{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e727557b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import gym\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "import torch\n",
    "from torch import nn\n",
    "import torch.nn.functional as F\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import sys \n",
    "sys.path.append(\"..\") \n",
    "import rl_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b9ed4fc8",
   "metadata": {},
   "outputs": [],
   "source": [
    "class PolicyNet(torch.nn.Module):\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim, action_bound):\n",
    "        super().__init__()\n",
    "        self.fc1 = torch.nn.Linear(state_dim, hidden_dim)\n",
    "        self.fc2 = torch.nn.Linear(hidden_dim, action_dim)\n",
    "        # action_bound是环境可以接受的动作最大值\n",
    "        self.action_bound = action_bound \n",
    "    \n",
    "    def forward(self, x):\n",
    "        x = F.relu(self.fc1(x))\n",
    "        return torch.tanh(self.fc2(x)) * self.action_bound\n",
    "    \n",
    "class QValueNet(torch.nn.Module):\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim):\n",
    "        super().__init__()\n",
    "        self.fc1 = torch.nn.Linear(state_dim + action_dim, hidden_dim)\n",
    "        self.fc2 = torch.nn.Linear(hidden_dim, hidden_dim)\n",
    "        self.fc_out = torch.nn.Linear(hidden_dim, 1)\n",
    "\n",
    "    def forward(self, x, a):\n",
    "        # 拼接状态和动作\n",
    "        cat = torch.cat([x, a], dim=1)\n",
    "        x = F.relu(self.fc1(cat))\n",
    "        x = F.relu(self.fc2(x))\n",
    "        return self.fc_out(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "230cb874",
   "metadata": {},
   "source": [
    "软更新公式：\n",
    "- $\\theta' \\leftarrow \\tau \\theta + (1-\\tau)\\theta'$\n",
    "- $\\theta$：主网络参数\n",
    "- $\\theta'$：目标网络参数\n",
    "- $\\tau$：更新系数（通常很小，如 0.001）"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80cb1a6f",
   "metadata": {},
   "source": [
    "### DDPG 核心组件总结\n",
    "DDPG 结合了确定性策略梯度和 DQN 的思想，特别适合连续动作空间的强化学习问题。这个实现包含了 DDPG 的核心组件：\n",
    "- 双网络架构（Actor-Critic）\n",
    "- 目标网络稳定训练\n",
    "- 经验回放\n",
    "- 探索噪声\n",
    "\n",
    "### DDPG 核心更新逻辑\n",
    "Critic 更新：最小化 TD 误差\n",
    "- 目标 Q 值： $$r + \\gamma Q'(s', \\mu'(s')|\\theta^{Q'})$$\n",
    "- 损失函数：$$L = \\mathbb{E}[(Q(s,a|\\theta^Q) - (r + \\gamma Q'(s', \\mu'(s')|\\theta^{Q'})))^2]$$\n",
    "Actor 更新：最大化 Q 值\n",
    "- 策略梯度：\n",
    "$$\\nabla_{\\theta^{\\mu}} J \\approx \\mathbb{E}[\\nabla_{a}Q(s,a|\\theta^Q)|_{s=s_t,a=\\mu(s_t)}\\nabla_{\\theta^{\\mu}}\\mu(s|\\theta^{\\mu})|_{s=s_t}]$$\n",
    "- 实现为：\n",
    "$$\\max_{\\theta^{\\mu}} Q(s, \\mu(s|\\theta^{\\mu})|\\theta^Q)$$\n",
    "目标网络更新：缓慢跟踪主网络\n",
    "$$\\theta' \\leftarrow \\tau \\theta + (1-\\tau)\\theta'$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1411bf1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "class DDPG:\n",
    "    ''' DDPG算法 '''\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim, action_bound, sigma, actor_lr, critic_lr , tau, gamma, device):\n",
    "        self.actor = PolicyNet(state_dim, hidden_dim, action_dim, action_bound).to(device)\n",
    "        self.critic = QValueNet(state_dim, hidden_dim, action_dim).to(device)\n",
    "        self.target_actor = PolicyNet(state_dim, hidden_dim, action_dim, action_bound).to(device)\n",
    "        self.target_critic = QValueNet(state_dim, hidden_dim, action_dim).to(device)\n",
    "         # 初始化目标策略网络并设置和策略相同的参数\n",
    "        self.target_actor.load_state_dict(self.actor.state_dict())\n",
    "        # 初始化目标价值网络并设置和价值网络相同的参数\n",
    "        self.target_critic.load_state_dict(self.critic.state_dict())\n",
    "        self.actor_optimizer = torch.optim.Adam(self.actor.parameters(), lr=actor_lr)\n",
    "        self.critic_optimizer = torch.optim.Adam(self.critic.parameters(), lr=critic_lr)\n",
    "        self.gamma = gamma\n",
    "        # 高斯噪声的标准差,均值直接设为0\n",
    "        self.sigma = sigma\n",
    "        # 目标网络软更新参数\n",
    "        self.tau = tau\n",
    "        self.action_dim = action_dim\n",
    "        self.device = device \n",
    "    \n",
    "    def take_action(self, state):\n",
    "        '''\n",
    "        这个方法实现了探索策略：\n",
    "            通过 Actor 网络获取确定性动作\n",
    "            添加高斯噪声使动作具有随机性，有助于探索\n",
    "        '''\n",
    "        state = torch.tensor([state], dtype=torch.float).to(self.device)\n",
    "        action = self.actor(state).item()\n",
    "        # 给动作添加噪声，增加探索\n",
    "        action = action + self.sigma * np.random.randn(self.action_dim)\n",
    "        return action\n",
    "    \n",
    "    def soft_update(self, net, target_net):\n",
    "        for param_target, param in zip(target_net.parameters(), net.parameters()):\n",
    "            param_target.data.copy_(param_target.data * (1.0 - self.tau) + param.data * self.tau)\n",
    "    \n",
    "    def update(self, transition_dict):\n",
    "        states = torch.tensor(transition_dict['states'], dtype=torch.float).to(self.device)\n",
    "        actions = torch.tensor(transition_dict['actions'], dtype=torch.float).view(-1, 1).to(self.device)\n",
    "        rewards = torch.tensor(transition_dict['rewards'], dtype=torch.float).view(-1, 1).to(self.device)\n",
    "        next_states = torch.tensor(transition_dict['next_states'], dtype=torch.float).to(self.device)\n",
    "        dones = torch.tensor(transition_dict['dones'], dtype=torch.float).view(-1, 1).to(self.device)\n",
    "\n",
    "        next_q_values = self.target_critic(next_states, self.target_actor(next_states))\n",
    "        q_targets = rewards + self.gamma * next_q_values * (1 - dones)\n",
    "        critic_loss = F.mse_loss(self.critic(states, actions), q_targets)\n",
    "        self.critic_optimizer.zero_grad()\n",
    "        critic_loss.backward()\n",
    "        self.critic_optimizer.step()\n",
    "\n",
    "        actor_loss = -torch.mean(self.critic(states, self.actor(states)))\n",
    "        self.actor_optimizer.zero_grad()\n",
    "        actor_loss.backward()\n",
    "        self.actor_optimizer.step()\n",
    "\n",
    "        # 软更新策略网络\n",
    "        self.soft_update(self.actor, self.target_actor)\n",
    "        # 软更新价值网络\n",
    "        self.soft_update(self.critic, self.target_critic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "16413cb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Iteration 0: 100%|██████████| 20/20 [00:12<00:00,  1.56it/s, episode=20, return=-1386.993]\n",
      "Iteration 1: 100%|██████████| 20/20 [00:21<00:00,  1.09s/it, episode=40, return=-1021.913]\n",
      "Iteration 2: 100%|██████████| 20/20 [00:22<00:00,  1.13s/it, episode=60, return=-953.469] \n",
      "Iteration 3: 100%|██████████| 20/20 [00:17<00:00,  1.13it/s, episode=80, return=-856.217] \n",
      "Iteration 4: 100%|██████████| 20/20 [00:17<00:00,  1.16it/s, episode=100, return=-507.282]\n",
      "Iteration 5: 100%|██████████| 20/20 [00:17<00:00,  1.14it/s, episode=120, return=-186.519]\n",
      "Iteration 6: 100%|██████████| 20/20 [00:18<00:00,  1.06it/s, episode=140, return=-195.258]\n",
      "Iteration 7: 100%|██████████| 20/20 [00:17<00:00,  1.14it/s, episode=160, return=-336.852]\n",
      "Iteration 8: 100%|██████████| 20/20 [00:18<00:00,  1.09it/s, episode=180, return=-306.179]\n",
      "Iteration 9: 100%|██████████| 20/20 [00:18<00:00,  1.10it/s, episode=200, return=-100.367]\n"
     ]
    }
   ],
   "source": [
    "actor_lr = 3e-4\n",
    "critic_lr = 3e-3\n",
    "num_episodes = 200\n",
    "hidden_dim = 64\n",
    "gamma = 0.98\n",
    "tau = 0.005 # 软更新参数\n",
    "buffer_size = 10000\n",
    "minimal_size = 1000\n",
    "batch_size = 64\n",
    "sigma = 0.01 # 高斯噪声标准差\n",
    "device = 'cpu'\n",
    "\n",
    "env_name = 'Pendulum-v1'\n",
    "env = gym.make(env_name)\n",
    "random.seed(0)\n",
    "np.random.seed(0)\n",
    "torch.manual_seed(0)\n",
    "replay_buffer = rl_utils.ReplayBuffer(buffer_size)\n",
    "state_dim = env.observation_space.shape[0]\n",
    "action_dim = env.action_space.shape[0]\n",
    "action_bound = env.action_space.high[0] # 动作最大值\n",
    "agent = DDPG(state_dim, hidden_dim, action_dim, action_bound, sigma, actor_lr, critic_lr, tau, gamma, device)\n",
    "return_list = rl_utils.train_off_policy_agent(env, agent, num_episodes, replay_buffer, minimal_size, batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "21bb0cbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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Nw/vvv5/tIREEQRAEkSOQgDJg5cqVWLBgAW6++WasW7cOhx9+OGbPno29e/dme2gEQRAEQeQAJKAMuOuuu3DppZfiwgsvxLhx47B8+XJ4vV6sWLEi20MjCIIgCCIHIAGlIxgM4qOPPsKsWbP4bTabDbNmzcLatWuzODKCyG+iURn+UCTbwyAIwiRkWTZlP+FIFJGoOfsyExJQOlpaWhCJRFBbW6u5vba2Fo2NjYaPCQQC8Pl8mh+CINLjxyvewzG/ewPdwXC2h2I5AuEINuxsQ7SPF5ld+7vxwid7NI9/Y8tebN/XZdYQiTwgHIliw842hCPRXrdt7w5hxh2vY9EznybcJhKVccWjH+GY372OKbetwvf+39txX6KC4ShOvvu/OHv5O/y2VzY14rYXPsMbm7MbqyEBZQJLlixBaWkp/xkyZEi2h0QQliISlbH2q31o6QxgT1tPtodjOe557Uuccd/beP6TPX16/OJ/b8JVj3+Md7ftAwB80dSBCx/8AFc/sd7EUeYG63e24fH3dpjmjmSLaFQecFfmwbe/wRn3vY2H127vddsNu9rQ0O7Hq5uMjQcA+LzBh/9sbMSu/T3Y1xXExzva8Mmuds02O/d3Y1tLF9btaEMwrAi3tV/twwNrtuGDb1r7d0D9hASUjqqqKtjtdjQ1NWlub2pqQl1dneFjFi1ahPb2dv6zc+fOgRgqQeQN+7oCYNeCFL7cEjq2tShO0Tct3X16/N4OPwCgsV35l4lY9ns+ccM/N+DGf32KT3e3975xjiLLMr6//B3MWfZfhAbwD+azBqW6srmh9ypLk0957+zrCiYcY0Ps/TWmthjjDyoBADR3BAz3AwBdgbDm30K3I53hmw4JKB0ulwtTpkzB6tWr+W3RaBSrV6/G9OnTDR/jdrtRUlKi+SEIInX2+tQPzXCUFFS6dLILSx/Ln/5QNPZ4pXzSFWD/5lc5VZZl7GxVxCH714q094Tw8Y42fLm3c0AdWyZm9upEjhHiNi2dxts3titjH1bpxdAKb+xxWtEufjaw9zn7t9iTXQGV3WfPURYsWIB58+bhyCOPxNSpU7Fs2TJ0dXXhwgsvzPbQCCIvEb91kn5Kny7dhSVdWO5E/w2/KxiGLMuQJMmEUWafzkAYPbFj1V+orUSTICqafAEMqywckOdtTEdACc5Rc0cA9aUFCfdXX+rh7zG9AyW+TnoBVegiAZVznHPOOWhubsbixYvR2NiISZMm4eWXX44LlhMEYQ7ihyQ5UOnTqRM+6RKIZUu6dU5WVFbcqQKX3YRRZh/x4pyKCMhVxLLWQApB5gaJ4igRosgTXSQRVsKrKy1ANJZJ078u4n70XxSKyIHKTa666ipcddVV2R4GQRwQiB+wUYuHe7NBf0tuzIHqNNhPVzCcNwJKvDjrnQ4rIQqopgTixGw6A2EuXFiuyWlPnAJq6hBFXqISnupABWM5qXgHSv29Q/dFoZgyUARBHOiIH5IUIk8ffWkjXQIsA8UdKHUqeT7loPLSgUrBDTL7OYHEuSaG+KUokVhlAqq2xIOaYrfyuBRC5J1+CpETBEEAoBJef5BlWSjhpd+INBKV+bd/VrrTOFB92GeuIl6cB0p4ZAJNeWyAhGCTbkZmMudLlmXN37RRmVGWZU0GqjomoPRiS/ydCacOKuERBEEo7KUQeZ8JhNUuzX1xi1hvHfHxomjq68y+XES8kOdPCW+AHKi42XGJn3d/dwihiFqKNxJ5Pn8Y3TGns67Ugw4/Kw8GEI5E4YiVB8Xj6wwokxrY+7SIHCiCIA50qI1B3xHLdn0p4Ymdn9U2BqIDlT8CShRNyfoT5TraEPnACMHG9sTZJD16UWckVln5rtzrhMdpR0WhCzYJkGWgtSsIQHk/d2vKyRH0hCK8ZxwJKIIgDmhkWda2MaAQeVqwsgYAzcUmVfzh+LyT6DrlUwlPfyHf1xnM0kj6h7aNQXYyUMkcKLatLdb9wlBA+dT8EwDYbRKqirQ5KP1zdgZC/EuCJAHeLE9uIAFFEERWaesO8QwOAIQjJKDSoVM3Yy7dJUpYE01AFWD6WXj5gn46vRV7QUWiMpqFAHeHP4yePgjndGFiprLQBSC5A8XO86jqIgCKgNK/L1kTzfpSD79Nn4PSv16dgQj/wlDkcmS9PxkJKIIgsor+g5gcqPQQxY4sp+9CBQQHiomx7nydhRcTHh6nculL1J8ol9nXGUAkKsMmCccxAEKQOUbjDyqNPWfvJTy2bTASRXtPSLON2AOKoc7E82v+ZXQFwtwRzfYMPIAEFEEQWUb/IRke4AVSrY4+95Su4NE4UAbtEPpSFsxFguEoz9YcWq8st2XFVgasfFdV5Oblr4HoBcXE5sTBpbHnTCza2HkdXF6AMq9TcxtD7AHF6N2BCqMjoAixbM/AA0hAEQSRZfQfkgO9wrzV0QuodIPk+hB5NCprRFNfe0vlGqxvkcMm4ZCaYgDWnInHhEtdqQe1xR7NbZkiGpX5c0xIw4GqKfGgmuWadH/nzNGqK1EFVE3sePQZqIPKFJeqU3Cgsh0gB0hAEQSRZaiE1z/0Ie90Q9+igAKAnlBE60DliYBiYqm62I3aEm2pyEqwdgI1xR7UlBg3nzSb1u4gwlEZkgQcFhNQ+zqVdgPGY1TGU1vs5mNs7tSe68Z2VQgy4hyo2L8jq5W1/jr9YXQyB4oEFEEQBzpxJTwKkaeFvmSXrmMUCGsvgu09IU1vqM48mYW3VxBQ1SVap8NKNPHu3W7VscmwA8XETmWhG3UlHtgkZZ3EfV3Gsxj3CjPs1DFqz3WDQQlP342cOVAjqxQB1RUMqyFyElAEQRzokAPVPzr6nYHSCiT969GdJ7Pw9nLnxp1w2RArwPJOtSUewUnL7HGwc1db4ta2GzDIXkWjaluSmhI3d5XEMfYEIzxUnsyBauYOlDKbrysQ5oKeQuQEQRzwNOs+hClEnh56wZRu24FASOtA6d2MrjwJkaslPHXdtWYLLufCSnh1JR4hRJ5pByrAnxOAUDqMf16x3FdVpIpVMW/G8k+FLjuKPU5+u5qB8kOW1dzViJgD1SGU8IopRE4QxIEO+xCuKlL6y0RJQKVFnIBKNwMVTu5A5UsbA00Jj13UO+P7E+U6rJxWU6KKk0wLKDEUDkAIr8c7UGq/KDecdpvgQKljbIj1gBLdJ0B1oPyhKJp8AS7eWQYqEFbbIRS6s9tEEyABRRBElmEXNvZhSg5UevS3hBfnQOWrgIpd7GsEARWKyGjrDiV7WM7BXp/aEg8XNJku4TXpZswlc6D28hKjso1RCU9tYVCgeWyBy47iWGlu0552AIpLxZwp5bHKforcTmQbElAEQWQNca2ruhLlw9TKbQyiURnrd7Zhd1tPn/fhD0Wwbsd+/P3d7Xh9c1Ov2zOBw5oq6kPkXzV34skPd2LHvu6EzyfSrG9emEJJUJblAemG3R9YE82aYjfcDnvC/kS5TCAc4b2sFAGliJMOfzijWbUmn5qBApQyKKCcu88bfNi6tyNuW+aOMfEjlvDYOWfbiDDBtXG3L/acHrgcNrgc2sWFc6EPVPZHQBDEActeIQtREvtAzGUBtWlPO0oLnBhc7tXc7g9FcO/rW/HMul3Y0+5HfakHb//yRNhsEtq6g3jx0wZ8Z8IglMYu2tc88TH8oSj+fP4RmuUo9nUGcPLd/+UXSZsEvLvoJO40AEAoEsWlj3yIcfUluGHOWC6gaks82L6vO84x+uU/P8GH2/cDAMbWFWPZDydhbF2JOnZ9Cc/HvuE7FIGbQknwooc+wJtfNOPIYeX49oR6nDttKNyO+BLL/q4gHnznG7yztQW3nH4Y71TNkGUZXcGIZobVl00dCEaiOLimmF9E+wLLO1XzC7sbbd0h7O3wY0xdcZ/3m4wnP9yJu179Ag/MPxKHDdIea3dQ+fLAAtnJWLdjP176pIGLPpfdhvLY/wucdvSEItjrC2B4VWYu6Y1CcF35VxnzUx/uxOPv7YDXZce6X58Mj9MuiCOtW9XhD8MfisDjtGNfTMxWJRBQX7d04b43t2qes8jtQGs4yPNTRTlQwiMBRRBE1vDFpiSXeV2wx1YejeRoJmVfZwBn3Ps2hlR48cYvZmrue+3zJtz7xlb+e0O7H63dQVQVufG3/32N+974Cvu7grjqxIPhD0Xw7Po9yj67gpoL6GcNPrR2BeGOCYVAOIqd+3s0AurzBh/e3NKMtV/tw/Wzx6Ajdg5ri2MCSudE7BHcsM2NHfj3+j0YO0cQUAlKeDXFbnQGwtzRWvVZE/7+7nbcedZEflEDFNHz9tZ9kGXgg2/244Nv9sPtsOPcaUNj+4/g7a0teGVTI57f0ICemOP10qcNcQLqV89uxD8/3IWXrj4Wo2uK8HVzJ2Yv+y+isiIaTjq0BvedewRsNgnt3SH8vze3oiMQhsMm4eDaYnx7fB0qDQSJLKvrx7FzWVPswRdNnXh76z50+MM4amQlKmLrvG3f14VPdrXjOxPr+7Xe2qrPmtDo8+OtL5q5gNrT1oMVa7bhiQ92IhiO4s3rZ2JQWYHh45t8fvzfS5/j37H3C6OmxM3HVVvixjf7urG3I4DhVYUIRaK4duV6dAbCOHJYOU4eV2coENd+tQ+VRS4cUtu7eBRn1QHAoFjpLRRrOdIdjKDJ58ewykIujphQLXY74HbYEAhHsdcXwNBKL1piiziz3KP22JTXJxiOoq7Eg8tnjgIQE1BdQd4QNRdKeCSgCILIGqwRn8MucQGVqyHyhnY/wlEZ21q6EAhHNA7LjlalPHbS2Bp8vLMNrV1BNPn8qCpSLm4A+EWjR7fOnCigmPN0xNByBMIRrNvRFldSY8HdQDiKtu4QF0zs4qbv28QE0GkT6/HiJw3o8GszP4G4ELnq1Hzd0oVAOIpwJIqH3tmGt7fuw6ubGvHj6cP59u096mLQJ4ypxhtbmrG9tYvv++S738LOVlXEeZw2+ENRw2zVh9+0IhiJYt2O/RhdU4TPGnxgb4dgJIr/bGzE9tZujKgqxFMf7cRf/vu15vG3PLcJcw6rwz0/nASHXXWr2rpD/GLPLtrsAr/8ra8AAKeOr8Ofz58CALjxX5/i7a37UF/qwZHDK+LGCQA+fwhfNnXiiKFlCUUWK6u1dCiva4c/hNl3/1eTW9vS2JFQQF27cj3e+WofJAn49vh6tHQGsH5nG+YcVse3qSn24Jt93by09fGONrzwSQMA4M0tzVj22pf48KZZKPOqYqWlM4Dz7n8X9aUFeHvhiYbPzQhHotjXpRVFxx1SjStmjkJpgRMPvf0NGn1+tHQGMayyEC2x93Bl7DxLkoSaEjd2tvagudMfE1DK/ioL48XuuVOHorUrgNMmDML3pxzE/85Y2wL2/SoXQuQkoAiCyBosMO6wqQIqV0Pk4gW/uSOgKeM1tCkXr7H1xYr71BXE3o4ADoPa+JAJFb/B4r2M/bGLT0Whi5cy9RkdccZVo8/PZ90xV0i7uLAsZMzY/VrBpHegmNATXa+uYIQLN/3MK/Z7udeJqSMq8caWZt6aYvu+buxs7YHLbsOPpg7BnPH1WL+zDb97ebNhg87WLkXcsZAx+/e7hw/Cpt3t+LqlCw1tPRhRVchF61EjK3DE0HKs2dqCT3a148VPG3DFzFEad6u1WzkmxQ2xx/ZZj7Vf7UNUlrG3I4DtQkaMNXncnyRgfvO/N+FfH+/GY5dMw9Gjqwy3YcfIBMO2li50BMIo9jhQX6o4YMm6oX/V3AkA+NuPj8SscbUAlNdUFGzVrNM3796tLn/S3BlAMBzFvq6gRkDt6wwiKgO723p4WS0RrV1ByLJSTmaCx26T8Ms5YwEAL29sjAmoQGzfMXEkfDGoKfZgZ2sPLw/v69SKLJHpoyoxfVRl3O36kl1xDjhQFCInCCJrsK7jTrst5x0ocX04vYhoEGYV8eaGMaHDMhtMqIiChXVVZrTGLtjlhU51ppPuucQ+TY3tfr6PWu5AqfsMhKNckBrdr4xHOS59Bq2swAmnXYode5gLN/2UeTU0LPRX6tR2kh5RVYhbzxiP6aMq+YVQH3qWZRltMaHDzif7d1Cph7s07LY9MdF62sRBuGHOWDx31TF8oVu2DYOVOUsK1IvuiWNr8e6NJ+H/nXcEAG1YnonQZHm8z/YoIedkEwbYMjhMXLDXckRVISYNKQOQeCHgcCTKRRE7LgBxbhdba46d85bYYw4fUopCl3Ku9X9TYqf5RN3EGUzAVxa5+d+oCHP0mChi/1YVquKIr4cX2xc7H6nkvxj6zuO54ECRgCIIImuEo8oHud0mwSbltgPVqXGgdOt6+ZSLaH2punRFk0/pMcQumqx0p128N4ED5XUJFx39c6m/79zfzctnRg6U+H82Lr1oY4JOfzErdDvgdSkXrX2dQS5CGnUCaq+Qj9GLPiYO2O0A+D71Qq4jEOavfWOsT5C4Xhprc8F6CLF/Bwm9hJjLxh7P9+1P3HyRzebSnjflNUrWFX9P7DmCYeP14ABVdOvXdqspdvPXK5ED1RJziew2yTDXxYjr3s0ySEVu/jel/5MKRtT3YG8LKjcnmTEHqK4Uc5728RKe4EAJLlk0KvNSdToCSt95PBdm4ZGAIggiazAHymG3wZHjIXLxAhvnQLWpF3pxodrWriAXOKx0JwoofRmLlZrKC10JF4oVn/urvZ38/0wgdWsyVsr/vS47Fw960cZKixWF2nJKocvOv/Vva+nit+sdMXWKu0fToFJ/H9+vO16wAKp4BEQHShWmg7iA0rpTYi+het02DCb+jARUYUzQsW2iUZmLu0RivjMQ5tsnE1CdegeK58tUt85oORRAFao1xcbODyPR8ifVxW7Y2N+U7jjE3l+9CSgxE2dEVXHMgeoKIhyJYn93fHmuRmim6fOH+HnVv+eSoX/tcmEtvOyPgCCIAxbmQIkZqEiOLibcqRFQ6gXaH4rwb92DSgt4dqjJF9C4NUw49YgCSl/C61QzUCWxJS70FzjxubfGMjIepw2lsfKUOE72/0K3gwsXvfPDLqZxAsrtgDdWAhIFVJPOMdkr9AhiIq61K4hgOBrXPwhQL3zdur5RrYKAauTlQnX6PMsjNbT70RNU+yENKhMcqJiYatQJKF+se3WJJz43w8bDwvJ+QRAlKic3CGU7JpCNYGXK/d0hhCJRjQMl9lIyQt/9OxF6AcUybNXFbti5A6UTUMKYmbhLRKoOVHNnAPu7Q5BlQJKAciFzJTbTZM9X4nGk1ZaCCV1AyWMVJMltDRQkoAiCyBpGIfJcdaASZaCYg+B22FDmdaqlGZ9f4y6wUpn47T/OhWEOlNfFBU2yEPnWmANV5HZwIaApRcUu4KKbpH9O5ozpA72FbjsXXaKAausOaYLHvExX7OG5qVBERktnIK6DNQB4Y9mVuAB9tyqg2rpD6Aqouav60gK0xUTQnrYe7kwVOO1cOCrbxUp4vjQcKMHJ6ApENCH/RBmoPYJAS+RABcNRPvMPUMqge7koEsudxiU89dwlL3Pp80VM8FQJmaX+OVDaGXh6KnkGKsBn61UIbUkAbTNN3sIgwf4SIb5ORW5Hv9pLmAWV8AiCyBpWCpGLwkPMrbAszKCyAkiSxN2WRA6UtoSnc6CEWXjsG/++zgC/AAbCEc3MMCZeCt0OLky6gxF+DkUHigkovevFLqb6KeWKa6Xs82tBQAH6rtKqy2SzSTzX0twREDJQqoBKJOTYDDzGxt3tCEdl2G0SqovdvPdQo8+vlu/KPJoLaS3PQOkFFMtAxTtQYpfrjkCIiy0gsYASHSh9GwiG/vhaOgPqMizF6kLAidbj4/mvXhwo9j5p7VLeJ2IJj50avQMlumapZ6CMx8Fe732dwYSz60QHSg2ZpyegRPGbC+U7gAQUQRBZhDlQdgu0MRDFjugs6S90/Nt2Z0BzoeUCKixmlLQtB5gLU1HoQmWRGzZJCQDv083i0iM6UIDqPHUZlPC6BIEljic+A+XgZZNtzZ2a+0RhqBdJNcLFcm+yDJSuhNfWrZ0Ntm5HG9+f3SahPlaqa+sO4evYeAbp1lITM1CiKPElcaAAUdRFNK9JIjc0FQdKnzVr7gyo6/GVuLlzFIrIhu0S2DmuLU0uoMT3SYvgAlUL2am4Ep4g4nsr4aXsQAlNLvViXPwywBcbNmhhkAyNA5UDAXKABBRBEFmENdJ02qWEeY1cQRMiN3Cg2MW7qsgFSVLci88afHw7wzYGurwSK/mUx0oglbryDLv4sCU9GIWxbs/sgsnC42zMeoHVLVxAmbCLL+Gposunc63YOGRZdTyYSGLZnkafX1j4Vr2gsqn1SolLPRetuun0H+9Qlp9hs++K3Q7+WCau6nXigm3bE4rA16OOWS3hGfcOKhLyYRoBlUoGKoGA0me89vr8wnp8yvpubDkWfWsI8bbaBM4Pw26TUBETLFv3dvL3UGWhmoHSx7T65kAlCJHH3qP7u4NcIOrfS6LI+zK2bl46M/AAreukn5GXLUhAEQSRNUI8A2WDPdZzKJyjIXLRMWE5IEBYWT7mkDjsNn5x2LCrnT/GeBaeerHeHythFTjtKIgJBXH2EqC6PQfXFPGAN6BmQpjAYPtls/wK3Q54nDawWIooEvwJQ+T2uF477PFsHG3dahdy5qgwp2JLow/hqAxJ0l4stZkj4fh1DtTHO9sAqCJJkiTUx3pBrYuJq3pdB2+P085FieiS+WIlvJIC4wuvODNQ7BKeSMyL+04UIteXZ79o6kSEnw/lXKutDOJFDDvHdb04UIB6zllvqjKvEy6HLbVZeEkcKFmWe52FV+5VvjDIScSR+GXgswZlm3QdqCI3lfAIgiA4kdjFxy44ULkaItdnWtg38wbeq0i9mNfqukMDYgbKOETeKpTvGDW6GVZiW4A6g1yRPl/UzR0oOyRJ4veLOR+W4YnLQAklPAZbN42V5pgTV1Ho4jkiNuZPdysX86oiN5zCsipOu5o5EkUpc6CYu8aOua4kvk0B6xo+yEBcMFHSIPSCSpaBAtQu13oHKpGY36PJQCVwoHQtKjbtUcR0ZaGLLzPDs0FGDlR7fPkzEWw/n8ccTyZmmeDVZ6xSdaA6A2H+fk0koOw2CRWxGXdbmpTSaqVBewI2pi2NyhiT9bYyQh8izwVIQBEEkTVY3skpzsLL0QyUXkCxb+ZGDR2NArf+UBSyLCdxoFgPKPUir15gYwKqQ72oGuWK1HxRzIHis/CMBZYynliIPEkJj8GWR9G3GRDLO/qLea3BLDLmlHUZOHDj6ks024plOn3JTu9AiduIQfJks/AAaFo8dPXiQMmyrOkzlaiEp3egmDskvjdqErQyEJ2wlByomBjZFHsO9hrYEnwpER2o7mAk7r3NYOMqEpqqGsHeO182MXcp/jVnsw65ICMHiiAIou+wvIbdZst5AcUuiPoyltgtm2EkGgDFrdCuhaf+n/WSEvvn6C+wqivh1ogJ5qAUCmFo5d+w5nZ9E0vRPfG67HALfXkK3XZNmRBQlxTRL+sizrJjYooJC6MMj1FPKlbC0wuoWo2A0gomIweKOYENBgKqpNcQubaEZ/Re9PWENfmmxBkorShhOTKxK7t+2R8GE6hi+4lkMMHE+oKxElqivymxEzmQOEjeW/6JwdxLdl6MynP6faTrQFEGiiAIQiASFULkOS6g2MWBLSLc5PMjEI7wvjbixV10Gdh6coBSxvMHjWfhMQdKLH/UCF3NledUA9u1GgGluFYss8T2y4RUkU5AMeEiOhFuh3qxlmKNCsWLlsthw8E1rISn7TlUK1wc9Y0fjRpB8maagoDkAmpQYgdKbJoJpONA9VbCU1s89DYLb49umZhEJTxWntSLNlFIiDMWRbhQTsF9AlQBxf522O+JZ+Fpx5yojMfG1VvPJv39VQYCSl8CNCrzJUOceZfISRxoSEARBJE1Qnwpl9wXUEx0jKgqBKBcXJra1Saa5cLMOLG8Vlfq4cfmD0UTzsITl3Fh6C+wYglPFBZMOBXq1plj/7IeUUW6Eh/LP9kkReh5hf1IkgSvIKBqit3cZdM7UOLx6i+URn2MvLqwezSqTuU/bFCpZts6zblUBVOxx2HozvD18ISZgqoDZSyguLAMhrnoBIy74jfoBFTCNgaxYxsee78wNCW8BCFy9jr31gOKoT/n7HfWIyuaZBYeYIYDpZt1Z9DjSV/WTj8DpZ00kQuQgCIIImtExFl4OdzGQJZlfkFkAqrJ59es1aZt6KheHOpKPPDESmP+UERXwot3oCqMlsDw6Ut42gxUohC52MZA/Jc102RizuO0x2bxMaeKCS71olVboq7f1hWMoFPoFC4eb7XuwmiYgeLLuSjj6PCH+XtheJUXHqdNeLzgQIluVGm8+wSopVTmQPWEIjxr13sfqLDmNTF0oGLrHrJSbqJZeCzAP7TCq7ldLOHpZ1kyGttZgD41AaUXOOw1YOZnsgwUkMyBSj4Dj6F3nHor4bnstoTl1ES4HXa4YuF7KuGZzDfffIOLL74YI0aMQEFBAUaNGoWbb74ZwWBQs40kSXE/7777rmZfTz31FMaOHQuPx4MJEybgpZdeGujDIYgDgpDBWni52EjTH4ryFe1HVcccKF/AcEFbQPttu7bEw9sS+MMRTYhc7IXU2mXkQKlLYHT4Q7wsFJeB8hhnnHgGyqUv4WmberJlWXhWKra9GByuKXaj0O1AcWybxna/0GRRHYsriRvHx6sbJ3PfCl12uB12fj6ritya9dLEkl19mbG4UJtpKuKWuU92mxSX6dKPp9Mf1nRqN+qKz/Z7ULkylsSNNCN8O6NlTQD13DT5tN3IU10Hj6EXOFX6El5cBio1AdVbF3KG6Ca5HTZDh0gcY2WRq09LsTBhTyU8k9m8eTOi0Sj+8pe/YNOmTbj77ruxfPly3HjjjXHbvvbaa2hoaOA/U6ZM4fe98847+NGPfoSLL74YH3/8MebOnYu5c+di48aNA3k4BHFAEOYlvNwOkYtdpYdrHCgmoLQXmFpNUNgDt0P54O8JRjQlPEAVEfsN2hiwi04wEsWXsXXvij3KjKi6JLPwmEDq1IXIi3QZKSbmWHhcv58iXQkPUHM54lp/epepWpOJincvvC7tOPfrypfs2PTntUgQcHrRymAOlM8fRncwzPNPydZPE8+b+FobifmGmAM1vFJ5H/RWwit2OzQOjXg+qoXAvdj4U+1un1qZK66EV6Qt4cU5ULru882d2h5c+zoDiOqWhUmGWMKrKnIbnmdRhKXbA4qhF/jZJm8E1Jw5c/Dggw/ilFNOwciRI3H66afjF7/4BZ555pm4bSsrK1FXV8d/nE7129I999yDOXPm4Prrr8ehhx6K2267DUcccQTuvffegTwcgjggUEt4uZ2BYhdDr8vOL+5NPj8+2q7tls1gnZeBWAnPyUp4UY0DBagOSavBLDyP085LHRt3K32EmGtRKSwWW5RAIPUaIg+rJTxAbS/g1f0LqG4IE0sN7X5hHTxdcNzAZREp4uv2xcRjl1Y8MuFkNIWfOU9GM/AAJSjOjqOx3d/rMi6A6uClVMKLOVDDKpXSXKISHnOgvC6HprGkWMoSX1+xjMfyW6m0MAAUkSbOoOQhcl4W127PRN/gmIvGhFIkKuPOVzZjym9fw/kPvIfd+3s0+0tElc5dMkLcR7pdyBkjq4sAxOfKskXeCCgj2tvbUVFREXf76aefjpqaGhxzzDF47rnnNPetXbsWs2bN0tw2e/ZsrF27NqNjJYgDEVa+yvUQuejkMCHh84fx2udNkCRg5pgazfZsAVxAcWyYQPGHI/DrHAvmeLAQtb4jONvPUx/uUvZXopZnDq4pgiQpCxmz8QFq/ye1jYG2RNfZiwOlF1yA4EDFxNF72/bxSQD6Cyzb1mmXNJkuhn4cahNNZduhMXEypNwb99iRVcpFlF1MjRBzUL0FyAFtI83eS3iKuBlWoVzEAzpBzOgWzr14fvTnSizjMYzWEEyGJElC7yf1PZSohMeE80Gx901zZwA+fwiXPPwB7nvjKwDAO1/t44tI9xYiFxcGTjS7rsBl5+6hUcg8Fe49dzJeueY4jK5J/NoPJLnhg2WArVu34k9/+hP+8Ic/8NuKioqwdOlSHH300bDZbHj66acxd+5cPPvsszj99NMBAI2NjaitrdXsq7a2Fo2NjQmfKxAIIBBQ3/w+ny/htgRBqPASnk3oRJ4FARWJyrjluU2YMqwccycfFHe/6OSUeJRlUfyhKCQJ+MNZh2PqiPgvahMOKsXejr04bFAJF1CBUCTugtsVUALUahlLe6GvKfbgq+YufBpzoMQ+SSvmfwtNPj+/EBYKWR5Zlrk4Y4KoWHBaADVE7tY7UEYCii0WHPv3yZigqyvxaDqNA6pIqCn28OVERPRZLV6+jGWnfnzUMDhsEs6aMiTusTd951CceGgNTjmsNu4+Rn1pAb5q7kJDux/umPuXzIFiJaGuQFjjEIrmkizLWPnBTuzan9iBkmWZl69E0c0clzKvk5dzGTUlbny5txMb97RjSEUBPtnVLqwhmJqAApRzvmt/DyoKVWcy4VIuOgHV0hHAtU+sxxtbmuF22HDZcSPxl/9+zbfrtYQnuE7JZtdVl7jR0Rw2bHOQCiUeJ0rqEgvhgSbnBdTChQvxu9/9Luk2n3/+OcaOHct/3717N+bMmYOzzz4bl156Kb+9qqoKCxYs4L9/61vfwp49e3DnnXdyAdUXlixZgltvvbXPjyeIAxWWMdFkoLIwC+/T3e34+7vbseqzJmMBFVTdBEmSMK6+BB/vbMPvvj8R358y2HCf9557BPZ1BXFQWUGvJbz2nhDYYZfrHJuzpgzG7rYeTB5ahtmH1eGUcapwGFRWwN0nQP3239IZ0ATf9dkRvQPliXOgYkLKKc7CUy6Mh9YX89uOHl2JK08YHXfsXEAlyPDwTuSxMldrrAs5y0BVFrlx1YkHGz52cLkXPzgy3pkSYSXAXft7+FgS9YAC1BJeZ5yAUgREMBzFNSs/xkufKl+kTxlXi1ExF4SJjK5AGKf98X84amQl7vj+RN43rFAo4Rk1FWW33fGfzbjjP5vVMbkdvQoXEf1ahIA6U1A/s5WV8FgQfndbD3a39cBlt2HlZdMxaUgZJg8tx6WPfIgyr8vQRRTxuuz8S0WyfFNNsRtfN3f1uYSXa+S8gLruuuswf/78pNuMHDmS/3/Pnj044YQTMGPGDPz1r3/tdf/Tpk3DqlWr+O91dXVoamrSbNPU1IS6urqE+1i0aJFGmPl8PgwZEv/NiSAILWGDWXjZcKB8PcoFfG+HH5GorJk1BcTPZntw/lS0dgd5SwMjPE47/4ZfEBMiPaEIekIsG2OPLaMR4SWsEo8jzs35/pTBCUWaHrEcxEQSa4oJJO5Ezhyy2YfV4Y0tzThtwiAAioMxZVg59rT18ND0dycOQpnXhRGVhbzUpmfy0HJIEnDE0HLD+726cbR1x7dw6A+sdcDO/d1cvCabNl/kTiCgYsJj3Y79eOnTRjhsEq6fPQaXHjuSZ6GYGNnS1IFv9nVjX1cQd3x/oqYLfDJBec63huCzBh9aOgPw9YQxsroQR4+uwtxJB8W9F5LBnkMUUIlag+gdKMbPTxqNSUPKAAAnjK3Bq9ceB6fdZugiikiShMpCN3a39WjKeXpmjKrCR9v344hhxu8Lq5HzAqq6uhrV1dUpbbt7926ccMIJmDJlCh588EHYbL2/+davX4/6+nr++/Tp07F69Wpcc801/LZVq1Zh+vTpCffhdrvhdueHoiaIgSScIyFyFmaOysoMJP30cf2SKKVeJ0q9qZcSWInMH1Jn4VUVubGjtRtdgbDhDLy+wLI/+7oCaO9R9ul12vkFsChBBoqJjMOHlOE/Vx+r2efKnxyFiCzz0pPNJuH4Q5J/Jk8ZVo6PbjpZ085AJK6NgUELh/7AhN2O1m4e+k9awuN9qbTuIKvOMcFxSG0xLjt+FADw9grBiHaNww5/GD1BdTaf12XHCWOqsfKDInzPwN2cNrISL19zXJ+OU4S5bmJXeLWEp902GJuFV1LgRLHbgY5AGIcNKuHHxkiWM9NTVawIqGTv4Z+fdDB+ctxILtitTs4LqFTZvXs3Zs6ciWHDhuEPf/gDmpub+X3MPXr44YfhcrkwefJkAMAzzzyDFStW4P777+fbXn311Tj++OOxdOlSnHbaaXjiiSfw4YcfpuRmEQSRHmEeIs9uGwOx+3STL15Asen2fW3g53EwAaWW8CqLXNjR2o2OQNg0AVHhdcFplxCKyNjW0h03ZnW2WawPFA+RJ76gOey2Pl0okl1I9Wv28fyXSQ7UEOZAtXbj0Dql5FhSkCxEbnyELHzNSnkOYVket105Z7KsfBEQnau9HX6+TE2h24ERVYV49drj+3o4KXH2kUPQ0O7HBdOH89vsCdsYxLJvDhu+NaICH2xrxe/PmpiW46Xn3KlDIAE49pCqpNvli3gC8khArVq1Clu3bsXWrVsxeLDW7hYblN12223Yvn07HA4Hxo4di5UrV+Kss87i98+YMQOPP/44brrpJtx44404+OCD8eyzz2L8+PEDdiwEcaDAQuTZXgtPXPi1yefHBGiXE2EzqsTO3OnAHJ6eUIRfvFgOpCsQNuxC3hdsNgk1xR7sbuvBV7GFZbWr2GuXUFFLeAM7IVvNQOkdKHMCwqyE1+jz87UKkzlQbocNDpsU1/cpzAWU8rtY2hUbfAbDUfQEVZunsd2vyc0NBLUlHtz+vQma21gRRk6QgXI5bPjbBUeiOxhOmhFLhXO+NRTnfGtov/ZhNfJGQM2fP7/XrNS8efMwb968Xvd19tln4+yzzzZpZARBJIJdoOzCUi7ZCJF3BkT3IL4rM2sL0NcGfuxbN8taAVoBtS92YTajhFVbopRSvoo13hQdKDEDJcsynxE40K5A/Cw84xYOfaWy0MUzZp83KLOikwkESZJQ6HagXXh9ADU7FBGyegxRQAXC2skBO1q71QB/Fps+2hLMbFUdKDvsNqnf4ulAJa/7QBEEkduwEHmuOVB6eCPNPpbwWIibhaUBdcZcZyCMHfuUcps+1NsXWA6K9fARHRAmXMJRWbno60LkA0WRUMKLRmXTQ+SSJHEXats+5Tz0tvyHURmPvReZ0LcJHbbtQm4vGI7yyQEA8E3sOQH1tc8Gif6mgkIJj+g7dPYIgsgarBGjPcsh8q6ANr+S6P7+lvDaYg6HwyahNJbJ6QyE8XWL4haNrO5/h2XWBdyohCe6IeKMs4G+kLIO5z2hCPZ2BBCVlSn3ZSYJKEDNQTFDszeXJZmA4h3z7drZaOy8BXUO1DYmXl32XmewZZLEs/CUsbpIQPULOnsEQWQNdSmX7IbItQ5UfAlPPwsvXTzcgQrx38XlQ75uVi64o9KY9ZQI5kCx5xLHLC6oKzaNzFYJDwA27VEahB5UXmDqBZ05UIxkbQyUMcWfA72Asutmdqsz8bSLRLPXs6+OpVlIBku5hCNqfzByoPoHnT2CILIGm4WX7RJeV1CchWfgQOk6eqeLW1fC8zhtXETsbvNjXyxEnayvVKrU6WYQ6kWfuIxKIEulHBbaBoCNu5WMEuszZRZ6AdWrA2VwP8vjie02RFyxWWuBBCW8vr5fzIJNqhP/pgLCUkLkQPUPOnsEQWQNNUSuCih9uWEgYA4TkCBEHlAXhu0LrNM3C0u7HXZeDvyiqQOAEv7uq8Mlom/WqL+Ii/mjbDlQkqQ6YcyByrSA6s2BMirPRnUOlJiBAgQHSjcLj/X6EhdjzgZGa+EFRQHVj7YFBAkogiCyiNrGQHUk9FPJBwJRQLV0Brgzpr+/r1PSC2IXUp8/xH8vciuOB7s4s0Vy+4vegdJfxAt5K4OQuhZeFpwIJuQ27Yk5UCa4byJD0nSgxHwYO2fhaC8OlJiBCscvKpzNGXiAMAtPjneg7DYJDhJQ/YLOHkEQWSMkTA9PNOV6IBA7UMsyeO8gfn+gfyU81kiTXceUEp5W2JgRIAfUDBRDP2Z1PbzsOVAAhBKmsiTKiKrk69uly+BydUaj0y712uuqSHCoWMCfuaHMwbHbE5fw/EEDATVAPaASYTPIQNEMPPOgM0gQRNYQZzc5YgHd7GSgwprf9TmoTpNC5Px3hz1O2KSzbEYyvC6HZsq+fszFQnhdvxbeQKIPWJtdwvM47cIyLk4eqE6E+HqUeLTuYCIHSpyF1xOKF1DZDpEblvAiNAPPLOgMEgSRNVgJz2Gz8a7JWXGgYhkn5iiIAkqWZR4y73sjTZvud3ucsDHLgQLURYWBxCFy7Sy8bJTwVNFmt0lxJTczYDmo3npAAdrzVFKg/F+dhRcre0l6AaUcQzBiLKAKs5yBMirhZbNsm2/QGSQIImuwRprZ7wOlOExsEdomIUgeCEf5mPpakolzoJy2eAfKxAyQmIPSh6OZUOjwhzUdqQcaUYwOLi/o1zpsiRiShoASXw9WwtM7UPZkGSgjAZVlB4oNV+tAqcu4EP2DziBBEFlDDJFzATXAs/AUh0kRUKyNQLPgQIkB8/4u5cJwO+2aqfwuuw2Dy81zYDQOlG7MRTniQIniYpjJ5Tt1vzEB5e59qRJNCY8JKF0GSt9IUzMLLxQvTLIdIjea2RoIZU805xskoAiCyBqhiLrKPSuPyLL2G3OmCYTVxoKsjCY20+ziLQz63lU6roTnsPP11wDlQq93N/pDrdDKQO+CcAEVzG4GSnTzRlSaX74DgMlDywAAB9f2ni8rNMhARXtzoFiIPKKGyIcI4fWsO1Dc1VVv4w4UzcDrN3mzmDBBENYjIoRzHUKX54gsw4aBWQJDdJhYkLlJWM6FBcj72gMKMC7hAYqYae8JmZp/ArQz8eJm4fFGmsIsvGyU8IRxmd3CgHHM6Cqsvu74uJ5QRhg5UGFdHyh9Boq5TYFQhLcxGFZZiK+a49chzAZGS7mwBaSphNd/SEARBJE1Qrw0oobIAeWCNVCmCGthUOC0c+GhcaB4F/K+D0gvoNgCs+yibdYMPEayEDk7jg5/SF0LLxslPFfmBZQkSSkvj5NaBirRUi5R9MTeR6JY64/oNgNmmEUMMlAUIu8/JKAIgsgafCkXvQM1gCW8TqFJZm1sId69Bhmo/pRjPI74WXiAGm42YwkXEW2I3NiBenNLszC+7DpQIzKUgUoH0S1K1AcqeQaKOVCqgOqP6DYDW5IMFDlQ/YcEFEEQWSEalXn2yG6TtA7UAAbJ2ULCXpeDZ4f2dQURikThtNt4Bqo/Aspht8FplxCKheZZCe+SY0egssiF2YfV9ecQ4jiovAA2SXG69PmrwwaVwmGTuKty/CHVfNr+QMLEhcMmaZpeZguxkSZb9qW3WXhiHygmTEQBlW0HyqiEpzpQFCLvLySgCILICMFwFDc/txHHH1KNOePr4+4Xl2xx2G1aByoycAJKFEjlXhcXOs0dAQwqK+AOVH8XhvU47AhFlH0xB2rO+HrDc9Nfqorc+NOPjkCxxxHXQHJEVSE+uulk+MMRVBS6MtI+IBWYuBhS4c2JJUXKvS7UlrjhsNniSni9ZaB6QhEuTIZWqG5a7oTI4zNQVMLrPySgCILICB9ub8U/3t+JDTvbDUWC+KGuLOUi3JcFB6owNsuutMCFls4A2rpDGFRWgA4TSniA0rqA7cs9AAGv0yYmFmalXidK0fvU/kwyeWgZqopc+E6ScQ4kTrsNqxYcD5sk8QWe2ftQ7Fcm4o4JP1+POhGhvtTDRXi2Q+SGS7lQBso0SEARBJERWEDZqMEgoK6DByjZEklSRFRUHtgMFG9TEBNIJQUOtHQG+MK/vh7l39J+lrnEUpo+E3UgMrjciw9+NavXJVYGEta+gJe+Ym9R1gYg0WLC7bH3CKCUTb8zcRA27Wk3fXmadGHGXjRKGahMQAKKIIiMwPI+olASCQtlOmesfOew2RCMRAdWQAkOFKAGiJlwYkKKXVz7ijgTLxt9l3KRXBJPIvqu+HwplwQh8vYeZfFpj9MGm03C3edMgizLWT8+o6VcyIEyDzqDBEFkBNYkMxQ2FkOsLCJJalYjG+vh6UPiTCj5/IqwYuUZ1huor2gcKBJQOQ0TUGF9iFyfgdKV8MTXNdviCYgXggB481RyoPoPnUGCIDICF1CR5A6UUwiPsyD5QAqobp0DVaJzoFh5pr8OVIFwcS0gAZXT6JdAiSTqRB6bycbeI7n2utqE7v6MYBbXP8w3SEARBJERWAkv2IuAEi9KvPHfAIbI4zJQsSnsPAPlZxkoM0t49NGby/DSl24Wnj4D5dZloHJOQJEDlVHoDBIEkRGY8xRO0JKAlfDE5oRsOntuOFCshBdzoPoZIhe/8VMJL7eJz0DFxL6u3YLYxgAYmNmV6WA3yEAFwrSUi1nQGSQIIiOEwr2U8GIXJbEPkf6b/0DQqWtToGagFOHUEctC9T9EbjP8P5F7OHQCKmEGSidCCnLsdTWahaeW8HJrrFaEziBBEBmBlfDCUVnzAc4wKuHZsxAiZ2vhsbXZmNMUl4EysYRH+ZPchpe+5OQlvDgB5cqt11UyWkyYSnimQWeQIIiMILYvMGplwEp4TuGilI0QOes07o01PRQdqHAkyh2qEk//SngF1MbAMqh9oJKHyN26kl421hRMhlrCU2+jELl5kIAiCCIjiO0LQgY5KHabuIwHm5AXzqoDpWagmHgSb+8rVMKzDvr3IXegEvSBYnhyzIHiswmjlIHKBHQGCYLICGL2KWyQgzIqizAHKjqQs/D4YsLMgVJn4bEguddl7/eacdRI0zqI6zJGozJ3S229ZqBy63Vlw41QBioj0BkkCCIjiALKqJUBE1Xit3qmpRLN3MsEXfoQudAHyqweUIAqmhw2KWsL+BKpIYbFI7KcpI2BVjDlmoDS97MCKANlJnQGCYLICGLZzrCEx3Ml8Y00B9KB6k7QibwjEEZbbImO/rYwANRv/OQ+5T7CWxKRqJykkaauhJdjpVm7QYicHCjzoDNIEERGEB0o1tJAhK0v5hQdKIPGf5lEluW4tfCKYyU8WQYa2vwA+t9EE1BnaOXaRZaIRyzhiQKqtwxUrjlQyRppkoDqP3QGCYLICJoMlMEsPB4i12SgBlZABcJRsKdincg9Tju/uOzc3w3ApBJerNxDs59yH40DJctqHyib9pLp0s/Cy7EQuS3JLDyXPbfGakVIQBEEkRHEsl3QYEFhNVcizsIbWAHVJcyy8wruActB7drfo/m9P7DSHTlQuY+YgYqKJbxeQuQ518YgNjzZoBO5m96H/YbOIEEQGUFTwjMIkYcMQuTsvwPVxoCvg+eyc/EGqDPxdnEHqv8ZqKLYPorc/d8XkVnErFM4SQZKXwbLtUaaRp39VQeKLv/9Ja/O4PDhwyFJkubnjjvu0GzzySef4Nhjj4XH48GQIUPw+9//Pm4/Tz31FMaOHQuPx4MJEybgpZdeGqhDIIi8oTcBFTboAzXQIXK1hYFW1GTCgTpqZAV+fNQwXDPrkH7vi8gskiTxGaHRZBkoe25noPRr+gFCBoocqH6Td2fwN7/5DRoaGvjPz372M36fz+fDKaecgmHDhuGjjz7CnXfeiVtuuQV//etf+TbvvPMOfvSjH+Hiiy/Gxx9/jLlz52Lu3LnYuHFjNg6HICxLb20MjKaGD1Qjzec37MGPH3gPXzV3AgAK3doLH8s8NfrMC5G7HXbcNnc8Thhb0+99EZnHLiznEk7gQNlskmYSRK7NsGQOFPs+ovS0Un4hB6r/5J2XXFxcjLq6OsP7HnvsMQSDQaxYsQIulwuHHXYY1q9fj7vuugs/+clPAAD33HMP5syZg+uvvx4AcNttt2HVqlW49957sXz58gE7DoKwOmIGyqivE1vexbCRZoYF1N/f3Y73t7ViW0sXgHgHigkmduExI0ROWAtFfMjaNga6DBSgCJFQRCkF51q+TQ2RK+MXv8i4c0zsWZHcerVN4I477kBlZSUmT56MO++8E+GwGhJdu3YtjjvuOLhcLn7b7NmzsWXLFuzfv59vM2vWLM0+Z8+ejbVr1w7MARBEntBbCc+oLDJQIfKe2PItrERXpHegCvQlvbz7rkn0glj+SpSBArRB8lwt4bEvJIGQ+ndIDlT/yatPhZ///Oc44ogjUFFRgXfeeQeLFi1CQ0MD7rrrLgBAY2MjRowYoXlMbW0tv6+8vByNjY38NnGbxsbGhM8bCAQQCAT47z6fz6xDIgjL0nuIPH4W3kC1MfCHIprf4zJQOseJHKgDD1FAhRNkoACdgMqxEDnTSMyBCsScMknS9l8j+kbOS9CFCxfGBcP1P5s3bwYALFiwADNnzsTEiRNx+eWXY+nSpfjTn/6kETeZYMmSJSgtLeU/Q4YMyejzEYQVCIptDAxKeMZLuWhLDpmiRyeg4jJQusyTGSFywlqIy6BEDMrNDFFA5VoGStJ1ImcOlMtu4/cRfSfnHajrrrsO8+fPT7rNyJEjDW+fNm0awuEwvvnmG4wZMwZ1dXVoamrSbMN+Z7mpRNskylUBwKJFi7BgwQL+u8/nIxFFmMqmPe34f298hV/MHoMRVYXZHk5KhHtZTDhsECJn/890iNwfu5DUl3rQ0O5HYS8OlBkhcsJa2HkLAPX9qF9MGNCWwnKuhMcEVOzPj2WgqAu5OeS8gKqurkZ1dXWfHrt+/XrYbDbU1CizXqZPn45f/epXCIVCcDqVD8RVq1ZhzJgxKC8v59usXr0a11xzDd/PqlWrMH369ITP43a74Xa7+zRGgkiFJz/YiRc/bcDomiJce7I1psH3pY2BPrORKVgJ77YzxuPx93fgh1OHau6Py0BRCe+Aw87FfJS/Hx22eOHhEppn5poDpW9jwB2oHGv4aVXyRoauXbsWy5Ytw4YNG/D111/jsccew7XXXovzzz+fi6Nzzz0XLpcLF198MTZt2oSVK1finnvu0bhHV199NV5++WUsXboUmzdvxi233IIPP/wQV111VbYOjSC4Y6LP7uQyod5KeGwtPFt8iDzzDpRyHscfVIoV87+FKcPKNffrBVORCY00CWuhinn1/Wg3yA25czgDlWgWHjlQ5pA3nwputxtPPPEEbrnlFgQCAYwYMQLXXnutRhyVlpbi1VdfxZVXXokpU6agqqoKixcv5i0MAGDGjBl4/PHHcdNNN+HGG2/EwQcfjGeffRbjx4/PxmERBAD1gy9gsChvrtLbYsJG64s5BsCBCkWi/LkTlVzEzFOx22E4+4rIb0TxYdSzjKHJQOWYMGF/WjLPQMWWccmxcVqVvBFQRxxxBN59991et5s4cSL+97//Jd3m7LPPxtlnn23W0Aii36gCykoOVG8lvJgDZRAiz6QDJQbIE3VjFpduoQD5gYnRLDyjDBQTI067pClH5wJ23VIu7HNEv4Yf0TfoLBKEBWAOjtjHJdfRNNI0EERG3Z0dNu2soUzAyneSlPibuCiaSEAdmLD3oij+DR2omGjKtfwTEN9XjX1+kANlDnQWCcIChKxYwhPGGjQq4RmEyAeikaY/qIzF47AnnMpdLDpQlH86IGHvRfG9a5SBYm5OTgoo3sZA+Z0cKHOhs0gQFsCSJbxoLyU8gxD5QLQx8MfOYbLAr9th58tykAN1YMLKX6KASpaByrUWBoDQxoBloMIsA5V7Y7UiJKAIwgKEwuwD0EIOlFDCS9bGQPxWPxBtDNgyLr0FftlMPGphcGDCHSjhvZusD1QuCigWIucZqDA5UGZCZ5EgLAB3oCySgRLXDwO0YorBXCanMAtvIELkLAPl6WXKOXOeqInmgYnDoIRn5ECxiQi5tpAwoO2mDggCKsfC7laFziJBWICQxUp4esfJeC28+KVc2P8zGSJns/B6cwxY9okWEj4wMcxAGYbIlfdRLmeg2JeZZGv6EelDAoogLAD7ELdKCU/vIBkJKKPeOtyBMnCszII1Je3tgsccKCrhHZgwjRGIvXftNslw0gHPQOVYE00gPkTOJ25QXzNTIAFFEBbAarPw9I0zjUp4IYNZeAPZxqA3B+rU8XU4qKwAR4+uythYiNzFrnOg7AlmbOZ0iFwQSlGhn1Wu9auyKuRNE4QFYGIjYJGlXFIp4bEV7u2GS7lkTiiyEl5vmZVzvjUU53xraNJtiPwlTkAlcG3cOdzGQBR9Skf1WNmcHChTIBlKEBbAaku5hFIo4fEQuZiB4n2gMjc2HiLPwQsekTvoBVQi0XHCmBocWl+C70ysH7CxpYokXOEjUZl/EaOlicyBHCiCsABWy0ClVsJjFyb1U35A2hiQgCJSgOWHghHl/WLURBMAxg0qwX+uPnbAxpUOogMly2ru0EklPFOgs0gQFiAfZ+EZhcjtA9FIMxYiz8XMCpE76NsYJMpA5TKi0xSRZcPlk4i+QwKKICwAEyChiJzRZU7MIqgTTEZLuRiFyPWdkzOBP8UMFHFgk2oGKpcRG39GojJfwJsyUOZAnyAEkePIsqwpgRmJkVxD34bAeDHh+D5QtgFxoFKbhUcc2KglPOuKDnHIsixTHyiTIQFFEDmO3s2xQhkvlRKeUU8ax0BkoIKpdSInDmyY48S6/yfKQOUymhKesDqA3UaXfjOgs0gQOY4+gG2FIHkqJTz+bVhcymUA2hj4Y2Px0IKqRBJ4CS9i3QyUJElgw1YyUNZ103IRElCE5WjtCuKdrS2QM5iTySX0M9qssB6eXvQlDZEPcBsD5kDlYudoInfIhwwUIOQKo4Lra0E3LRchAUVYjoVPf4Jz738P721rzfZQBgS9+MhECc9sMRrWjdko0xQyyJbY+dpdGXSgKEROpIA9LgNlzfeLTZiYYTTzleg71nxHEAc0X+7tBAB81dyZ5ZEMDPqSndklvGtXrsdJd73FhYUZMHHEujTrXTRA/TYs9qRh3/IzuBQehciJlLDpM1AWFR1M90WiMm9wSxkoc6CzSFgKWZbR5PMDAJo7AlkezcCQaQdq9edN+Lq5C9/s6zJtn8GYAip0OzS/ixj1pBnIRppuElBEEphLE4pYW0DZNQ4UZaDMhAQUYSk6A2F0xzIsLZ0HioDShchNzkAxIaNvPdCvfUa0zSqNl3JRbhOXcrEPRIicHCgiBWz6ELlFRYeNl8VlykCZDAkowlI0+VTR1NIRzOJIBo54B8pkARX7UNXPnOsPbMxeV2IBFYnEz8JTHSjThgJAm/GiTuREKvAMVC9r4eU6TAhGZXHmqzWPJdcgAUVYCla+Aw4cByo+A2VuCY+5PWY6UKxk542V8Iz2HYrGf7Nn35bNdKD2dvgxfcnr+N3LmwHQYsJEavA+UFafhWdTS3hhykCZCp1FwlKIAqr5ABFQmXSgolEZLG5k5BLpeXPLXpxy91vYsLMt6XYsNF4Yc6CCkWjcTD+jELkjAyHyDTvb0ejz45WNjQDUDBQ5UEQy8qWNgVjCixiUzYm+QwKKsBTaEt4BKqBMzECFBKcnFQH18sZGfNHUidc+bzK8n4W/mYPkFXotia0M5AQLm/JZeCY6UJ2BEACgtTsIWZapjQGREnGNNC0roJR/I1F1SSirHkuuQZ8ghKUQHaiuYATdwXAWRzMwZHIWnrgwsT6sbgRzvzoD8ed9yX8+x5G3v4aG9h6+rwKXQ9i/ehzi8xqFyM1spNkZUM5Xe08I/lCUO260lAuRDObcBGKC26q5IfY3JcugPlAmQwKKsBR7O/ya3w+EILl+GRQzS3iiaNI3vzSCibcuAwH11pZmtHYFsWFnOx9zoSBSNM8lCCiHQR8oM9sYdPqVscoy0CgIcFrKhUiGI86BsublkpfwxMWELXosuQadRcJSiCU84MDIQel7KJkpoETRlMosPFY+7ArEu2BMNHUHw9xtEoPaogOlEVAGJTwzQ+Si2Nu9v4c/D+VAiGTYeB8oVvbK5mj6jurqqhkoKy6MnItY9C1BHKg0tisOArvoHggz8eLXwjOvhBdOs4TnZw6UQemUZYu6AmG+X5fDBlfsyqMRUML/jQSUmX00xXLjnjZFQBU47ZAsuDgsMXDYhfA1YF3Xhv15RWWhDxSV8EzBmu8I4oBElmVewju4thjAgdGNPJOz8EQBlVIJjztQBgIqNq6uYIS7UU67xJv2hcLGJbxMtzHQCKh2RUBRgJzoDb3jZNXgtU0oi1MJz1zoLBKWYX93iLsk4+pLABwYDpS+tJapEl4qs/DUEHm8C8acse6AWsJz2m28TUFQ40Cp34RFJ8jBP+zTOoyksAwUoDpQ1AOK6A195smqro1dyEBxN41KeKZAAoqwDGwGXkWhCweVeQAcIAIqg400xbJdarPwYiLJqIQniCuxxxMTUGGDlgn6D/KMZKCEsTbESsAkoIje0DtQNqsKKOFLidXX9cs1SEARloEJqNoSD6qK3QAOjFl4mVwLT9vGIHUHSl/CC0WifF9iiNxpl+AyKOElypVkoo1Bh+BA7RYyUASRDJsuI2dVB0rSLCYc+2JDJTxTcPS+CUHkBntjM/BqS9yoKlIE1IEwCy+TGahEM+MSwcSbvg+UOCbxPqfdBqfDoIQXTe5AmdtIU3Cg2pgDRRcQIjl6wWRV14Y5aZEEzWuJvkOfIoRlYD18aos9qGYO1AEgoFgJj130zSzhiaJJXyo0gs3C84eimvyUX5gZ2B2MaDJQDj4dXCzh9eZAmTcNT3TLemgdPCJF9CLDqg4Uy0BFozL/m6UMlDnkjYB68803IUmS4c8HH3wAAPjmm28M73/33Xc1+3rqqacwduxYeDweTJgwAS+99FI2DonQoZbwVAfqQFjOhQmPIrcTQOZC5KnkjsTyYbcgmvQOlJqBktQMVMSohKf7ls/LDSkfQq+IIXIGCSiiN/SZJ6tmoGzCl5IwdSI3lbwRUDNmzEBDQ4Pm55JLLsGIESNw5JFHarZ97bXXNNtNmTKF3/fOO+/gRz/6ES6++GJ8/PHHmDt3LubOnYuNGzcO9CEROlgTzZoSD6qKXAAOjOVcWOmr2KNU3M3MQKXTB0qWZY37JTo7WgcqzMfstNvgcsT3gRqoELksy+g0eH9QBoroDXueZKBswpcSq/e0yjXy5iy6XC7U1dXxn8rKSvz73//GhRdeGNcwr7KyUrOt0+nk991zzz2YM2cOrr/+ehx66KG47bbbcMQRR+Dee+8d6EMidLAeULUlHhS5HXDHLsz5HiQP6QWUmSW8SOolvHBU1jhDCQVUINJrGwMeZrUbl/DMikB1ByOQDXQhCSiiN/QlPKsu5WIXQuTs7506kZuDNd8RKfDcc89h3759uPDCC+PuO/3001FTU4NjjjkGzz33nOa+tWvXYtasWZrbZs+ejbVr12Z0vETviCU8SZJ4Dirfg+RM2BS5mYAyMUQeTb2Ep39esReUvoQXEtoYJMtAxV+kzHWgjBp+AhQiJ3onXzJQTPcpJbzYFxuLHkuukbez8B544AHMnj0bgwcP5rcVFRVh6dKlOProo2Gz2fD0009j7ty5ePbZZ3H66acDABobG1FbW6vZV21tLRobGxM+VyAQQCCgXsR9Pp/JR0NEojLvOl5TrPSAqipyY9f+nrwPkjOxkQkBFRH7QIWTl/D0S8h0JyzhRXi2ymmXeAkvrFlMOFbCSyCgorJSfuvvcisdsTEWexzoDka48+VxkQNFJEcvoCybgRKWpGEOMs3CM4ec/xq2cOHChOFw9rN582bNY3bt2oVXXnkFF198seb2qqoqLFiwANOmTcO3vvUt3HHHHTj//PNx55139muMS5YsQWlpKf8ZMmRIv/ZHxNMdDPM//jKvUnLlrQzyPEjOSl9FPANl5iw8wRXqxfXxxzlQqoASc1ldwTAXeQk7kSfoiCzmTsyYiccC5MVuB8q9Ln67x0ECikhOvvSBYmJJLNFTBsocct6Buu666zB//vyk24wcOVLz+4MPPojKykruKiVj2rRpWLVqFf+9rq4OTU1Nmm2amppQV1eXcB+LFi3CggUL+O8+n49ElMn4hQs0yz7lYisDfygCt8Nm6kK1bDHhEo/5s/DS6USuF25ih28xlyXLavNKRUDFl/DCidoYCIIqIsv9/oBiJTwmPtl7pYAcKKIX8qUPFBOCAXEBb8pAmULOC6jq6mpUV1envL0sy3jwwQdxwQUXaMLhiVi/fj3q6+v579OnT8fq1atxzTXX8NtWrVqF6dOnJ9yH2+2G2+1OeYxE+rASkShOqmMz8XJFQH3T0oW5/+9tnDi2Bnf9YJJp++UOVAZKeKIDZbSYcDTmAtlsUtIMlF83M7CtWwn2uxwSHDEHKhSOfy5nhh0oVsIrdDvgEgLrHgd9AyeSoy/Z5ZMDZVUxmGvkvIBKl9dffx3btm3DJZdcEnffww8/DJfLhcmTJwMAnnnmGaxYsQL3338/3+bqq6/G8ccfj6VLl+K0007DE088gQ8//BB//etfB+wYiHiYgBKdg5ICRSD7enKjjcFD73yDtu4Q3t/Waup+Q/oSXoZm4YkO0fqdbXji/R144ZMGTBxciscvPSpOQCXKQAFKewlAcZiYcAlpMlDJQ+SAOQKKO1BuBxegADlQRO/o2xhYVXSwYWtLeNY8llwj7wTUAw88gBkzZmDs2LGG9992223Yvn07HA4Hxo4di5UrV+Kss87i98+YMQOPP/44brrpJtx44404+OCD8eyzz2L8+PEDdQiEAczhELMrrKTV4Q9lZUwi3cEwnl63CwDQEzRP4ABquJsJgFBEWdPKjA90oz5Q72xtwbn3v8dvf29bq9IDSi+SxAxUAldMU8IzmPGXqI0BYE4rg05BQJUXChkoamNA9EIycW8lWAmPHCjzyTsB9fjjjye8b968eZg3b16v+zj77LNx9tlnmzksop+wJUTE6eclBcrb12fQaXqgeX7DHp776TZZQOkbaQLKh6EZLkrYoLnlVy1dAIChFV7saO1GJCojEI72UsIzPmaXQ+1ELs7yUzNQiUt4ZrQyEAVUJQkoIg3ypY0BL+FFmCssmZrRPJChIABhCZirI174inPIgXr03R38/z2hCM8OmQH75igKKLPKeKIDxUQNe74JB5Xy+3qCkTiRJHaA12egGOIsPKOFi/XNCW02CeyzPWLUATNN2Cy8Qt0sPGqkSfRGvjTStOkyUOQ+mUef3hE9PT3o7u7mv2/fvh3Lli3Dq6++atrACELEb7AILCvhZTsDtWFnGz7d3a75htpjYqsBJjw8Tjv/8DMrSK7pRB57HibOClx2nl/qDkUMHCjjWXgijoSz8IxD5IDqQpmZgSr2OFBBDhSRBvo2BnZr6id1Fl7YuGxO9J0+nckzzjgDjzzyCACgra0N06ZNw9KlS3HGGWfgz3/+s6kDJAhA7UEklvCYI5NtB2rVZ0rbiznj1VYXZpbxmPBw2W28hYNZ6+GJuST2POybqtthg9etCI3uQDhOQGmXcknkQAklvBRC5OJtZs7C02egyIEieiN+nUZrCg92GOzvmxwo8+jTO2LdunU49thjAQD//Oc/UVtbi+3bt+ORRx7BH//4R1MHSBAA4I8JEvHCx2bhdQmdr7PBjlbFjZ04uJSPz8wgORMeLocgoMwq4UUSl/BcDhu8sePpDkbinrNLzEAlGI8rUQlPWOpFj5kCSizhVYiNNGkpF6IX8qWRpk3nWlv1OHKRPn2KdHd3o7i4GADw6quv4swzz4TNZsNRRx2F7du3mzpAggDEELmYgVIzQZ0J1jwbCHbtVwTU4HIvCmOOjdhksr+I1rs7NgvRtBJeNL6NQYA7UHYeVO8ORrjrVRI775pGmgkcKIfdxpdy0ayFl2ApF8BcAcXGWOxxoLxQ7QtHJTyiN/JlFp5dV8KjJprm0ScBNXr0aDz77LPYuXMnXnnlFZxyyikAgL1796KkpMTUARIEYJyBctpt3PHpyOJMvF37ewAAg8sLNILDLEIRQUA5zXag4kWN6EAVxlon9ITUEl5lbAkdTQkvrM7wEXHaJX6buJQLE1xuAydIXQ/PRAfK5UBlodrslvpAEb2RP32gtCFyWsbFPPp0JhcvXoxf/OIXGD58OKZNm8a7dL/66qu8SSVBmElPUA1SizAXqr0nOzkofyiCvbG1+AaXe+F1xgRHpjNQmXCgYm0GmDhzO1SB2hVQZ+GxMLbYxiCgu4/htNkMM1Ciy6WHCa6wGSU8YSmXApcdP5o6FKdNrNe0NCAII/LFgWIlPMpAmU+f+kCdddZZOOaYY9DQ0IDDDz+c337SSSfhe9/7nmmDIwiGUR8oQBFQezsCWXOg9rQp7pPXZUe51yk4UOaNhwsoRwZKeJpgt0GI3KVmuthzMpFk1EizotDFBaXDJsFmk+CMiT7R7VIdxfjvcDYTZ+GJfaAAYMmZE/q9T+LAIH/6QCn/BqmEZzp9bqRZV1cXt8Du1KlT+z0ggjCCL+Wic6D4ci5Zmoknlu8kSeIZKLPaGESjMndunHbJ9Fl4YrNK9gEbFASbNyY8uoNh7kwx96YnFOEd0dnrU1mkOjvsg9pl0MaA7ctj4ECZmoGKuWTiMi4EkQr6+Q1WdW7iMlAWPY5cpE+fKl1dXbjjjjuwevVq7N27F1Fdx+Cvv/7alMERBMMoAwWIzTSz40AxATWk3AsAKIiV8MQZav1BbDPgdKiBbLMyUEatBXg+SZiF12XgQAGKsCr2OHkbgwohZ8RKdyxzERRLeClkoPoroKJRmTtQhSSgiDSJ7wNlTeHBuo6rJTzKQJlFnz5VLrnkErz11lv48Y9/jPr6emoLT2Qcvhae7oJbkuVeUDv5DLwCAOAlL7NKeKLAyUQGKmLUB0p0oMQSXoh1RHfCbpMQicroCkRQ7HHGuVNsvAB4CS8kjNloViXDLAElzhIUZ2wSRCrow9ZWFVB8KRc+m9eax5GL9OlT5T//+Q9efPFFHH300WaPhyAMSVTCK85yN3K1hKc4UKLgMANRdGSkjUFEbGMgxxYNZqF1u1DCU/tAeZw2FLrs8PnDXKSoDpQqoJgDxUp4YrlQdLn0mCagYi6g3SYZPg9BJENv1Fh19pp+9QKrCsFcpE/viPLyclRUVJg9FoJICMsUueMyUNl1oHbFOVAxwWFSBioozJyx2yS1jYFJ+w/pREo4KiMQiS/hdQfDggto55kiFiTXz9AD1AwUE1JiCS+pA2VSiLwzoLwnitwOcsmJtMmXWXjsrR+kDJTp9ElA3XbbbVi8eLFmPTyCyCSJMlB8Pbysh8i1DlS3SY099ba76W0MdB3cQ5Gopg+UppGm0N6AOVMsY8R7RBmU8Bx2gxIed6CSlPD62QeqkwLkRD/IFwEVHyK3ppOWi/Tpk2Xp0qX46quvUFtbi+HDh8PpdGruX7dunSmDIw4cVn6wA0VuJ06bWG94P7vgxs3C4xmogS/h+UMRNPMeUIoDZXYjTbGJJoC0S3gPvb0NrV1BLDhljOH9+l5LoYjMhZKSgRJLeKroKXRrw/LqLLz4ELnRYsJcjGUwRM6aaJKAIvqCvpGmVZ0bNQMVa3ZLGSjT6NMny9y5c00eBnEgs78riIXPfAqX3YZTx9fxxm8iifoGFWfRgdod6wFV6LKjzKuMgztQZpXYYmUv5jylsxaeLMv47YufIxyV8ePpw1Fd7I7bJpkD5XbYhLYMYUFA2VDkVkt7siwbztBzOlgbg/ilXHg5MEkjzf6X8NQmmgSRLvniQPFO5NRI03TS/mQJh8OQJAkXXXQRBg8enIkxEQcY7T0hyLLiqvjDEe56iCQs4RVkz4HiLQwqvDxjU+gytxO5WsKLCSiegerdgfKHotxh8icQdHoHKhyRtSU8oRN5IKS6Ruw4OwNhjRumyUDZmANl1Ik8sQNlS0FAybKM1q6gxvHSQy0MiP6g/yJnVQeKlnLJHGmfSYfDgTvvvBPhcPbWHiPyC7HclUh4JCrhZbMPlD5ADqglvC6zMlD9KOGJrRRCEePtxVl4bDuxVOcVBGHQsIQX1oi5Yo+Dl+zUDFR8CS+ZA9VbiDwcieLalesx5bev4aKHPsA3LV2G27HXoJgEFNEH9ILJyBm3AqwhKPtzsqoQzEX69Mly4okn4q233sLw4cNNHg5xICJe6LuDEVQabNOToITHQ+SxtfAWPv0Jtu/rxt8vnsrDy5liZ6s2QA4IbQxMK+ElCpH3vn9RmIYiCcRINHkJz8tKdaEwIrF9eJxqaa8zEOEz6uw2CU67sgBxW3eolxJe4qVckoXIQ5Eorn7iY7z0aSMA4PXNe7HmyxYMKvPAH4pi8tAy/OlHk+Gw2wQHihYOJtJH30jTqsJDL/zslIEyjT4JqFNPPRULFy7Ep59+iilTpqCwsFBz/+mnn27K4IgDA40DlUB4sAuuftZWsRAi7w6G8cQHOwEAXzV3YUxdcSaGy0nmQJkdInfFjjudWXjiuQwm2F4vrOJD5GxWobov0YHqFhwoNrZCV0xA2ZOV8Fgn8vQaad7y3Ca89GkjnHYJN3/3MKz6rAlvfdGMb/Ypr8V/Njbivje+ws9PGo2Pd7QBUF1KgkiHfMlA6cPwToseRy7SJwH105/+FABw1113xd0nSRIiEfNWoifyH9GBMirhRaNqSJkJFAYTUMFIFJsbO/jte9p7Mi6gGtv9AID6UlVAeTOUgWLNKJngSCUDJYq4YKISns6B8oci3OpX+kCps/DYBcTtUDNQXcFwXE8n5vjwDJRD60BFo2rOypNmI81XNjUBAJb+YBJOP3wQzps2FJsbO9AdDOOTXe249fnP8MfXv8Q3+7rw2udNcNgkfHuC8cxOgkhG/Cw8a2aH4pekseZx5CJ9ElD6te8Ioj+IF3oj50Z0W/Qh8kKXAzZJqe9v2NnGb29o85s/UB1MOHgFUVdo+lIu+gxU6iW8Hk0JL7UMlJjdcgklvJ5QhJcw3E4bd6A6AxG1HBcbGxORLgdrpKnNQIliLpkDpQ+4y7KMtu4gAODIYeUAlC9sh9aXAACOGFqOD7/Zjxc/bcC/Pt4NAPjt3PGYEtuWINLBZpMgSQCrJFtVd+RLGD4XsehbgsgnuoQLvdFsMfE2vWNhs0m8z48ooBrbe0weZTzibDUGD5Gb5UDFBE5ciDwFB6onlEKIXCdSOkUBZbdpxCHb1u2wq20MhFl4TAyx14OX8GJXnqisuErJXk9A/YCP6sbWEQjzMZR7XXGPkyQJv507HjWxdg1XzByFH04danjcBJEKogtlVQdKH3miPlDm0ScH6je/+U3S+xcvXtynwRAHJj26ELke5vQ47ZJhMLykwAmfP4wNu9r5bXvaM+9AGQko5r4Ew1FEonK/cxMh3XOUFih5nv0xJyYZ3Sk5UNrb2dp2dptyrvX2P8D6Q6nZMzWfxhwo4xIeGwebgceeQw97Tn2IvK1LmSjgcdriSrmM8kIX/n3V0fi8wYeZh9QYbkMQqWJj9jYsnIEiBypj9ElA/etf/9L8HgqFsG3bNjgcDowaNYoEFJEWXQGxhBdf+mKlKKMp7wALCfdgmzCdvWEgHSi7KKDUMXYHw/0OMOvbGNSVegCo+atkaDJQ4USz8PQOVCxAHns+m02C12XX7MvtsKGyUHF5WjoDmjXyALXvkr6EB7A2CdqSnx7mYH3drG1PwESjkfskUl9aoMmlEURfcdgkBIX/WxH9OpCUgTKPPgmojz/+OO42n8+H+fPn43vf+16/B0UcWIizxYxLeLELdALXocSg03TDQDhQkXgHyu2w8UxWTzDSbwGlzsJTPgSZgOoIhNHhDyXdf08qIfJYidBhkxCOyjwDJTa4FAWUI+Ya1ZQoAmpvR0CzRh6ghsj1JTxAEZ16waXntIn1eObj3fjnR7vwi1PGcLepNUUBRRBmIZbw8sWBclIJzzRMk6IlJSW49dZb8etf/9qsXRIHCGJwOVkJz6hnEGA8Tb2hzQ+5n4vR9kbAoIQnSRIv45mRg9J3Ii9yO/jMwyZfcpGoKeElaGPAZuGpHceV10J01cRyGRNJLGfUGQhjf5cibJggYgKHnQebTeKP6wlF4gSXnpljajC4vADtPSE8v2EPv50FyMsLqS0BMTCIAWzLCqg4B8qax5GLmOrltbe3o729vfcNCUKgp5dZeP5eSnhsORcAfL23nlAE7T2ZXR/PqIQHiL2g+j8Tj/VOEp+jPuZCMZftxU8acOVj6zQBcEDr7CXKQLH9szGzfYiisFBYWkcMijPRtTO2pA0TuD+aOhQ/OW4kzj9KDXCLiw/35kDZbRLOP2oYAOCRd7/hQnh/LANVRg4UMUCIYkMvRKwCzcLLHH0q4f3xj3/U/C7LMhoaGvD3v/8dp556qikDIw4cugShYVjCizkWiYLDJYIDdWh9CSLRdrR2BdHQ7s/YxVaWZV4W0zspvBu5mQ6U8Bx1pQX4oqmTC6h7Vn+BL5o68e0J9ThtotrzqCeFpVxYryX9EjRug5mF4u2SJKGmxI3t+7qxI9bEks0QHFRWgBu/fajmeQrddrR2xfpGhdRGnYn4wZFDcNeqL7Bxtw8f72zDEUPLeQaqggQUMUAwAWWTrLuUi37YmV6h4UCiTwLq7rvv1vxus9lQXV2NefPmYdGiRaYMjDhw6K0PVLJ10wBtBmpkVSH2dQZiAqqH9wgym3BU5v1h9EKAla7M6EbOM1CiA1WiBskjUZl34d7Tpg3OaxtpGpcz2f7FRYMBtfM5oA3Gi8KqplgRUDtjHdkTlVgB1cXqEtoeJHKgAGVR4u9OHISn1+3Ckx/s1Aioci+V8IiBgblOVi575UtH9VykTwJq27ZtZo+DOIDpTUAxJ8edQgZqZHUhdu3vxqY9PuzJYDNN0dGJF1DmLeeiXwsPUIPkDe1+7Gnr4S6VPjifUiPNKFvfTlvCcxu0ZlBuV0VPTbEyjh2tTEAlFkTi4sMhYU29ZJwwthpPr9uFrXs7AQD7u5USXnkhOVDEwMDEhpVFR76s6ZeL9MnLu+iii9DR0RF3e1dXFy666KJ+D4o4sOjurZEmK+EluEAXaxyoIj6FXT/Vv8nnj8sJ9RVxbTl9BsprYgbKaKZfPW9l0INv9iVu3aBtYxAvoGRZ5iU8r66Ep+1tpZ53UfSwvFmHP1506REzULzxZgJHkcFeRyYMWVidZuERAwWbQGrVJpqAgYCiEp5p9OlMPvzww+jpie+z09PTg0ceeaTfgyIOLLo1jTTjRUdvoeOSAq0DVV+mCIw9gqDY3xXEcb9/Az/861pTxswEiU2K/0BiQs8MB0o/Cw/QOlDa3ldawdjdS4hc7AFVkNSBEkt46v+ZgGIkdaB4h3Y1A9WbAzUo9jo2+ZRSJXOgyqiERwwQTDhZ2YHS6yVyoMwjLQHl8/nQ3t4OWZbR0dEBn8/Hf/bv34+XXnoJNTXU/ZdID6MSXjAcxQfftMY6V/fWxsDB768r8aiz1IQS3q79PQiEo9i42wefv/+z84xaGDCY25JuiHz9zjYc+dvXcP//vua36dfCA1RnptHn1zSb1DtQ/l76QInr4Hl0ZceEJTynNgMlkloJLyJ0Lk/uQFUXuWGTFKHX0hngbQwqqIRHDBBMa1hZQMUvJmzdY8k10spAlZWVQZIkSJKEQw45JO5+SZJw6623mjY44sCgOxA/C++BNdvwu5c349ffGcdvS1TCO6S2GC6HDdNHVsJmkzQCgyGW7r5s6uz3ArNBg3A3o6APGShZlnHLc5vQ0hnAPz/ahUuOHQnAuI0Bc6DaukP4vMHHb9/bEUAoEuViq1tcC8+gE3lYWBTcq+8DldCBEgRULMxudJ+eQqFEyM5Pbw6Uw25DbYmHZ71aqYRHDDD5kIGiRpqZIy0H6o033sDq1ashyzL++c9/4vXXX+c/a9aswY4dO/CrX/0qIwO9/fbbMWPGDHi9XpSVlRlus2PHDpx22mnwer2oqanB9ddfj3BYWxJ68803ccQRR8DtdmP06NF46KGH4vZz3333Yfjw4fB4PJg2bRref//9DBwRASjCQSw1MdGxrUUJDm9u8AkOlLGAqi3x4P0bT8LfLjgSgJoR2tPWw3sIiaXBL5ri83vpoq6DFz8mr1PNQMmynJLj9Z+NjVgfWwx5695O3mzSKANV4nFwUfPxjjZ+uywrIorR21p4ogMV1wcqYSNNMUSudaDcqThQwTACvbyeIuy13NbSxV0/CpETAwVzb6xc9op3oCgDZRZpOVDHH388AGUW3tChQ+PW2MkkwWAQZ599NqZPn44HHngg7v5IJILTTjsNdXV1eOedd9DQ0IALLrgATqcT//d//8fHfdppp+Hyyy/HY489htWrV+OSSy5BfX09Zs+eDQBYuXIlFixYgOXLl2PatGlYtmwZZs+ejS1btlB5MgP4Q1GIDcPZRd/Xo1zIG31+XjZKdsEV+z0xhyYQjmJ/dwgVhS6NA7Wl0UQBZfBtTpyFt+Q/m7FizTYs++EkfGfiIMN9hSJR3PnKFv57OCrjy6ZOjD+o1DADJUkS6ko9+Lq5iwssttxKQ1sPDipTHLjeZuGFYg6UJKnukVHAW9NI05GkhJdSiDzMxVkyx4qhuIlt+GyP4rQ57RJ3swgi0zjs1negqJFm5uiTFB02bBjWrFmD888/HzNmzMDu3bsBAH//+9+xZs0aUwfIuPXWW3HttddiwoQJhve/+uqr+Oyzz/Doo49i0qRJOPXUU3HbbbfhvvvuQzCoWP/Lly/HiBEjsHTpUhx66KG46qqrcNZZZ2n6Wt1111249NJLceGFF2LcuHFYvnw5vF4vVqxYkZHjOtDp0oXGmdvEuog3tvt7DZHrcTvsqCpSBBXLBYlujCkOlIEzxPC61T5Qr33WhHBUxi//+Qm+bu403Ndj727HtpYuVBW5MGlIGQBwwWDUxgBQnRlAEU+HDVL6XYlB8t5m4Ynr4Dl1pUhXokaawmtQ7nVpPoyTOlA8RB7p1VEUYcf5WaxUWeZ1DegXN+LAJi/6QMXNwrPuseQafRJQTz/9NGbPno2CggKsW7cOgYBSNmhvb+duz0Czdu1aTJgwAbW1tfy22bNnw+fzYdOmTXybWbNmaR43e/ZsrF2rzMwKBoP46KOPNNvYbDbMmjWLb0OYiz5ozR0ovyigUpu1JVKnC5KL6+2ZW8IzEFAxsdDcGcDXsVlyXcEIrnz847g2DdtauvC7lxX36epZh+Bbw5Vs1qY9ypJIoQRCra6kgP9/eGUhBpWxKf9qkLy3xYRZCwOHzRY3kzDxLDz1dptN0szES+ZAeQUHignilByo2HExAUVdyImBxJYHGSh9xY4cKPPok4D67W9/i+XLl+Nvf/sbnE51SvHRRx+NdevWmTa4dGhsbNSIJwD898bGxqTb+Hw+9PT0oKWlBZFIxHAbtg8jAoGAZkaiz+dLuC2hhTlQ7EtSTyiiyQ11BMLY16k4iIlC5EbUxQLOLBPEOmwDQEtnEPs6A4aPS5VkAoqN8+Pt+wEAlYUuVBW58HmDD39+8yu+XSgSxTVPfIyeUATTR1bivKlDMS7mJDHBwMLf+rC66ECNqC7UtDYAgHAkqhFNhiW82G0OuxRXiky8Fp52HGIZL5mjVMRcuYC6mHA6DlQbtTAgsgATG1YWHZSByhx9OpNbtmzBcccdF3d7aWkp2traUt7PwoUL+ay+RD+bN2/uyxAHlCVLlqC0tJT/DBkyJNtDsgzMcRKdBX8oivZuNXi9PdYsMtUSHqCuj9cRE2L6UuEXTcbltFQJJFhIGFCn/XfEXK/JQ8vx85MOBgB8ultdbPtPr2/Fhl3tKPE4sPQHh8Nmk3DYoFIASgkvGpURMGhjAKgOG6AsXzOINZ2MOW49OqcrZLCUSziqlvD0DlTCEp4uNF9d7BHuS+JACSF17kClIaAYNAOPGEhsvIRnXdGhd8+ohGcefVrKpa6uDlu3bsXw4cM1t69ZswYjR45MeT/XXXcd5s+fn3SbVPdXV1cXN1uuqamJ38f+ZbeJ25SUlKCgoAB2ux12u91wG7YPIxYtWoQFCxbw330+H4moFOmOOUMVhS7si01T7wyEufgAgD0xVyWdEl5RrDcU65Kt70D+RVMHpo+q7PO4k2agdCHnwwaVYHC5InD2dqgZpcfe3Q4AuG3ueF6CG1lVCLfDhq5gBDtauxEyWEwY0AqL4ZWFvBcWK+HpS6PJZuE57LY4geZOYS08AKgpSdOBCoa5A5VKCY+dFwbNwCMGErWNQZYH0g9oKZfM0ScBdemll+Lqq6/GihUrIEkS9uzZg7Vr1+K6667D4sWLU95PdXU1qqur+zKEOKZPn47bb78de/fu5bPlVq1ahZKSEowbN45v89JLL2ket2rVKkyfPh0A4HK5MGXKFKxevRpz584FAESjUaxevRpXXXVVwud2u91wu90J7ycSw9oLFHkccDtsCISjaO4IaGbmMdJxoJigYMKJ9Zpis9W29DMHlbSNgU5AjT+olK8bt9enlA79oQgXjDMPUWd3Ouw2jK0rxoZd7di0x8edM32IvE5XwnPGviGzEp6+B1XAKEQem4XntCUv4XkTzMIDUi/hsX10BiJpTQqoKnLDYZO4W0YLCRMDiSqgrKugaDHhzNEnAbVw4UJEo1GcdNJJ6O7uxnHHHQe3243rr78el1xyidljBKD0eGptbcWOHTsQiUSwfv16AMDo0aNRVFSEU045BePGjcOPf/xj/P73v0djYyNuuukmXHnllVzcXH755bj33ntxww034KKLLsLrr7+OJ598Ei+++CJ/ngULFmDevHk48sgjMXXqVCxbtgxdXV248MILM3JcBzrsQu912eF12REIR9EkNMAUSU9AKRdalqXqjDldEweX4t2vW/FFP1sZBFMo4THGH1TCZ8K0dAYQicr8GD1OG0oKtNuPG1SCDbva8buXN2NHazccNgkjqgo127CSHQCMqCxEJKY4mzsDCIajcQLKOAOlOlDJSnjatfC0r0FNiiW8vjpQdpuE2hIPdrcpzhp1IScGEnteZKC0v+vdZqLv9OlMSpKEX/3qV2htbcXGjRvx7rvvorm5GaWlpRgxYoTZYwQALF68GJMnT8bNN9+Mzs5OTJ48GZMnT8aHH34IALDb7XjhhRdgt9sxffp0nH/++bjgggvwm9/8hu9jxIgRePHFF7Fq1SocfvjhWLp0Ke6//37eAwoAzjnnHPzhD3/A4sWLMWnSJKxfvx4vv/xyXLA8G3y2x4e/v7sd72xtyfZQTEMVUA4evm40QUCxC3ZnrITHnK7JQ5VZbluaOniTzb7ABImRCBAzQxWFLtSVeFAZW5YkKgP7ugJ8oeO6Ek/ctPxxsRzUjtZuAMDi747j3dUZ5YUuXD97DBaeOhblhS5UeF1w2W2xZpp+9IS0JUvjEl4sRG7QxiCVWXhAGg6UW+2NxV7zVF9PsVxZRhkoYgDJhzYGtJRL5kjLgQoEArjllluwatUq7jjNnTsXDz74IL73ve/Bbrfj2muvzchAH3roIcOu4SLDhg2LK9HpmTlzJj7++OOk21x11VVJS3bZ4rXPm3DXqi/ww28NwYzRVZr7ZFlGW3fIchkRJmy8LjsXHo3txgIqnVl4xboMFGtjMPGgUthtEjr8YTT6/HHCJFVSaWMAKPknSZJgl4DKIjeaOwLY6wugKTY7sFa3HAoAjKsv4f8/84iD8OOjhhmO4coTRvP/22xKc80drd1oaPcjENIKJqOlXHgbA7sUVyJMvBaezoHSZKB6d6AAYH9sTbtkbQ9ExHIllfCIgYS3MbBw77G4EDkJKNNIy4FavHgx/vznP2P48OHYtm0bzj77bPzkJz/B3XffjaVLl2Lbtm345S9/mamxHvDop6qL3P3al5h82yq885W13CmNAxUTHolLeKm/XfksvACbhac8T5nXhWGVXgDQLMSbLsnWwhOn/Y8/qJT/n7k1zR0BNMVeQyMBNf6gEkw4qBQzRlXi/743IeXGkeISNt3B3h2okNAHKpkD5XLY+IduvAMllvASC1y3w8ZLCWxNu1Rm4QHaILnVviAQ1oYJJyvPXIsXUFTCM4u0HKinnnoKjzzyCE4//XRs3LgREydORDgcxoYNG6g78ADALpBGDg1bVPaTXe2YMaoq7v5cpUtwoLxO5e3ISnjVxYpjw0irhOfRlvCYA1XkdmBYhRdfN3dh+75uHD064S6SEkjWB0pwoMYP0gqoTVBKbOwY60rjBZTbYcfzPzsGsiyn9Xclvj/YfovcDnQGwlzwfdHUgV88tQHXzjoEUVl1oPTfSvXHVeCyo8MfjhNQtSVunDyuFi6HTXPceiRJQqHbgQ5/mGevUhXE9RoHigQUMXDY82EpF93QrSwGc420pOiuXbswZcoUAMD48ePhdrtx7bXXkngaIOq5A9UTdx9zGFh5xCqw6faFBiW8MbXFmm37MgtPX8IrdNsxrFIJZLP+Un0hWQnP5bDxktXEwaKAUmfiMZfNyIFipPt3Vc+7kfu5s1da4NSM97XPm/DJrnY8u363pg+Uvk2Cy64918xV07tMkiThbxccifvOPaLX8YllPKN9JTwuQUBRJ3JiIOEOlKUFFGWgMkVaAioSicDlUj/AHA4HioqKTB8UYQy72Pr8Yc3SJIAqoNq6QnGPy2VYh/ACIUTOxMXwKq8mm5NWHyi3KqBkWeYlvEK3A8NjJbzt+7r7PO5kAgoA7vrB4fj9WRMxpMLLb2N5ob0dooAyr/2FKLCZgCqJCSj2/vDHbu8KhLV9oHS2vr7j+KiaQtgkYGilF31F394hdQdKEYY2SRXGBDEQMLGhFyFWQi+Y9H/rRN9J69NIlmXMnz+ftwXw+/24/PLLUVionWL9zDPPmDdCglPscfKSTKPPj1HVqnhlIeG2Hos5UCHVGWIX2P1s2Y4CF2qKlSnskmScN0oEa2MQjETh84d5YLrQ7eAO1Df9caAiihBJNKZTDotvvMoyUJoSXhIHKl2Y0GgQ1g8siQkOVjbzx4RfVyCi9oEyCJHrj+tvFxyJ1q4gDirrW+geiHegPCk6UAfXFmFQqQcjqgvjVpYniEzC2xhYuOwV50BZ+FhyjbQE1Lx58zS/n3/++aYOhuidulIPtu7tRGO7VkAFeQnPog6U0x6XoSktcKKuVBFQBU57WiUt8WIthtK9TjsPke9o7U47Z8TozYEygi170uQLoMmXeBZeX1FD5H4eIuclvNj7g5VMu4NqFslutJiwzh3yuhxx/a3SRf94/XMke9xbN5xg6ZlQhDWx58FSLvovHVYuR+YaaX0iPvjgg5kaB5Ei9TEBpZ+Jx0t4Vs1AuR1xbQpKChw8DJ1O/glQvjkWuuzoCkZ4psrrssNmkzC43AubpMwAbO4MaGaSpUqyRpqJYCW8rXs7+eNrMlDCa+kMoL1HEdKlQglPlmXuTHUFI4hoOpHrM1DmXzAK+5iBAqj5H5EdmPiwsujQf/Gw8rHkGvSpZDFYyadRFyQPWdWBijklBS57XEamtMDJjzedHlAMVsZj5TLmgLgcNj41vq85qGRr4SWClfDY8jIVha60RERvVBS6+Hi+aVGOqyzWN0mWlb5PbJHh7kBY6EQuwelIPgvPDArd6rE67RKFWYmch+l2K2eg9OYZtTEwDzqTFqM+QS8oFghu7w71q8P2QKPOwnPAoxNQJR5VQKVa7hFhgWPWc6lIuIAPZzmolr7loPpWwtO6TWaW7wBlRhx7f3zV3AlAdaAARfSxdei6ghGhE7kt7kPVTGHHEB2oVPNPBJFN2N+FlV0bykBlDhJQFqMuFhTW94JijkgwEr8OWi6j7QOlL+E51RJeHy64rBeU3oEC1NlkbLmUdAn0oYTndti5IwQAdSaW7xh6gV0iCKhQWCjhBcJqGwO7QQkvEw6UuCRMHxxFghhomPiwsuigEl7mIAFlMXizRJ9xBgqwVi+o7oC4mLA2I1Na4MTRo6sw/qASfH/K4LT3zUp4LEQuBstZK4Nv+lrC64MDBWjXjjPbgQK0iwwDakd2gDlQyvkOR2UutB02W9wso1QW+k0X0YHKxP4JwmzY9woriw4KkWcO+hSzGHUJupGzPAsAtOV4DmpnazfuWvUFOvwhdIfUpVziSngFTlQUuvDCz47Fxcekv0h1ceyCzdwYr1DC628zzb5koADt0ieZEFD6zuYFLjt3l0KRKM9AAeBBc6WNwQCEyAWBnE5PL4LIFrY87ANF2UPzoK50FoM5UPu6gvCHInx2WiisOlC5LqDue2MrnvhgJ3w9Id6fyevWlvAkSRVAfYVnoGIOlOiADOtnM81QnwWU6kAZLePSX+p1fZq8LjucdgnBiDJmv4GAstu0faCcdikj/Za0DhSV8IjcZ9qICjz+7g4cNbIi20PpM+KfssMm0cohJkICymKUFjjhcdrgD0Wx1xfgWZ6ghUp4rPz4wicN/DavUzsLr9jt6PdFnAmolk7lfBSJGahYh/D2nhDauoMoS3OJEFbCc6fp1FSXiCW8DGSgdK6W12WHy2FDVzASE1Dq+8THHSjtYsKZEjfiLDxyoAgrcOLYWmy4+RRLN3AV3TNyn8yFPsUshjLTinWcVlsZiBmoXO8F1dqljK+lU2km6XIojRzFEp4Yfu4rRW7tPsQSntfl4AKmLzmovmegMlvCqy/TlfCcDi6OAmFjB8phkzQZqEwEyAF9CY8cKMIaWFk8AVrRRPkncyEBZUF4L6iYkxOJyogKnQtyvRcUE1AMNjtLdKBKTRBQ+nXT9EuJDKtQclB3/Odz3PbCZ9i6tyPlfZsRIjdzGReGPkRe4LJzARWKyIYZKLtd0qyPlYn8E6AVsBQiJ4iBQZyFp19xgOgfdDYtiH6quug+AbmfgdqvE1Bs9p3YLFOcPdZX9AJKP8vvsINKAADvft2KB9Zsw1nL16YsovoeIlcElNMuoTzNsmEqlHmdGnHCSniAIvpEB4qX8Gw22GxqY8u+9NxKBVHAkgNFEAODpMtAEeZBAsqC6GfixQuo3C3h+UMRdOn6VDHnqSDjDpT2ov2LU8bgnh9Owk2nHYoJB5WirTuECx54P26GoxF96QMFAGPqilHkduCIoeUZKQ1IksS7rAPMgVKepysY1jiVvIQXu59tlzEHykVtDAhioJEkiQfJKQNlLvQpZkFUB0rJQIktDIDcDpGzsdltEsbHHCAvL+GpF9iSgv7PbyjWuVh6B6rQ7cAZkw7CJceOxMMXTcXI6kLsaffjskc/6nXffS3hlXldeGfRiXj0kmlpPS4dxNKg16mW8Dr8Yc12TMiy+1kZL1MZKHKgCCI72PNgTb9chASUBdF3I9c7ULmcgWL5p3KvC6eMqwOgTm8XS3iZcKD0i9mKVBS68PCFU2GTgA0727C3I7ELJctyn0t4gFKezOTiuCxI7rIr4Xw2xg6/8fuCfbg6Y9tlyh3yambhkYAiiIGCtS6gDJS50Nm0ICxH09yhzGILhrUCipVmchEmoCoLXfjxUcNw2oR6XHrsSADKhZxd7M3IQOlD44Xu5BftIRVeDK9SguWfNyTOQoWjMthyg2577gkBFiRnJVEm1nw9YcPt2bdSXsIbgFl4VMIjiIGDBcnJgTIX+hSzIOzbO8vhxDtQuVvC4w5UoRPlhS7cd94ROGFsDb+flfNKvWY4UNp9JHOgGOPqlbLiZ3t8CbcRBWumxEZ/YBk55uixTJMvgQPFBBZbODVTfaDsNomPidbCI4iBg7nMlIEyl9z79Cd6RZxVBYAvCstmW7QLHb5zDdWBMm4iyS6wmZiFp3ekjBg3SBFQnzekJqCcObjI6KBYCY+VzNgYfQmcSfahyt5XmRSFzAUkB4ogBg6mm6iEZy50Ni0Iu8AFYs4Tu6BXxKbFy3Lii2W22S84UEawspMZGSi3w6YROF5X767HocyBSiagYufdJuXmB9JRIytx7MFVmDd9OAAkDJEz2Dly2DJbwgNUF5AyUAQxcNgoRJ4Rcu/Tn+gVt+BAybLMS3het527LG05KqBaY+XFigQ9kL49vh7DKr04fEhZv59LkiRNGS8VB+qwmID6urlT0zNJpK8z8AYKr8uBv188DfNmDAeghsMTlfBY6Y4JrUy6Q2wmJC3lQhADB8tAUQnPXOhTzIKIF+5gJMrbGDjtNpTFskO5moNiJbyKQmMB9YvZY/DW9SckvD9dRNGkb2NgRHWxG1VFLkRlYEujcZC8rz2gsoW7FwdK3wcqkwKqiJfwyIEiiIHCppsoQpiDNa4AhAbxwh0MR7kD5bLbeHfrXG2mqYbIze/CbQTLQbmE6fzJkCSp1zIeP98WEQHqLLxUHajMHddRIyvhcdow4aDSjD0HQRBayIHKDCSgLIjoEATCUZ7J0ThQXblZwmPjMsth6g0moLy9tDAQYTPxEgXJWQnPKkFopyMWIo+V8Ap1WTDmQDky3MYAAK47ZQw23HwKxtQVZ+w5CILQwkPkNmt8ZlkFOpsWRJIk7kIFw1GEYhd0h11CWcyBytUS3r5eSnhmU+RWBGVhCuU7xqG9tDLoTxPNbKDvA1VZ5NbdL2m2y3Rpksp3BDGw8BA5lfBMxRpXACIOsZUBa2PgtNtQHnOgcrGZpizLXNgNlIAqiTlQvTXRFBFbGUQN2kEELZaBYuPsiYXiK4u0594+gCFygiAGHlrKJTPQJ6VFYRe5gC4DlcsOlM8f5v2pyhPMwjObYi6gUnegRlYVwuWwoSsYwY7W7rj7c30Wnh79sjH6HlzOAepEThBEdqAMVGagT0qLIjpQ7ILutEvcgcrF9fBYgLzQZR+wPkBFMQGVSgsDhsNuw4hKZUkXIwEVsJiA0o+zUuf+sV5WFTFhpS/xEQRhbSRqpJkR+r/kPZEVuICKRDRtDFgn70AomvCx2WKgZ+AB6nIuqTTRFCnTlUJDkSj+9PpWHH9IlZqBssiHkd6BqijSCyjl0/Xakw/GlGHl+M7E+gEbG0EQmYdKeJnBGlcAIg528RZLeE6HjX/DCEdzT0DtFxYSHiimjqhAkduBY0ZXpfU41gmdCaj/fdmMP67+Ere/+LkFS3jaD81ij0Mj/tiHak2xB2dNGUxdwgkiz7BRCS8jkANlUdxO4wwUu1iGI7m3Fl42HKgjhpZjw82npP3BoRdQzR0BAEBju99yAko/zgKnHV63HcHu2OxNmtpMEHkN+/xz0t+6qVjmbN5+++2YMWMGvF4vysrK4u7fsGEDfvSjH2HIkCEoKCjAoYceinvuuUezzZtvvglJkuJ+GhsbNdvdd999GD58ODweD6ZNm4b3338/k4fWJ8Q2Bqyk5LBJ/GLIRNVAs62lC8te+8JwGZTelnHJFH351qUv4bFMWUtnEIGwcmxWEVD6Ep7Hade0daDuxASR33AHiv7WTcUaVwAAwWAQZ599Nq644grD+z/66CPU1NTg0UcfxaZNm/CrX/0KixYtwr333hu37ZYtW9DQ0MB/ampq+H0rV67EggULcPPNN2PdunU4/PDDMXv2bOzduzdjx9YXNG0MWAbKYeN5lrDB9Pv+8vrmJvz8Hx8nXFMNAH7x1AYse+1LvPBJQ9x9+we4B1R/4A5UTDi1xf4NRqJo6VTcKLdFMlD6rFaB065p60C2PkHkN7SYcGawTAnv1ltvBQA89NBDhvdfdNFFmt9HjhyJtWvX4plnnsFVV12lua+mpsbQxQKAu+66C5deeikuvPBCAMDy5cvx4osvYsWKFVi4cGH/DsJEWDPCxCU88x2o5W99jfe3teL4Q6rx/SmD4+7f2dqNj7bvBwDsi4kMkX1ZKOH1FSag2nqUMYtL4+xp8wOId3ZyFadD70DZNOsCWuU4CILoG8x4onK9ueT12Wxvb0dFRUXc7ZMmTUJ9fT1OPvlkvP322/z2YDCIjz76CLNmzeK32Ww2zJo1C2vXrh2QMaeKpo1BRG1joJbwzHeg2FpqO/fHT+0HgOc27OH/7wzEL1xrKQcqVmZkJbw2oS3E7v09AKxTwnPpbHu3zoGi7sQEkd+wEh79rZuLZRyodHnnnXewcuVKvPjii/y2+vp6LF++HEceeSQCgQDuv/9+zJw5E++99x6OOOIItLS0IBKJoLa2VrOv2tpabN68OeFzBQIBBAKq4+LzGS8BYiaqgIogFFbbGLA/kExkoDr8iijaFRMQep7vRUC1DnAX8v7AHahuloFSHajdbdYSUHqHqcBp1zhQ9K2UIPIbVsKjcr25ZPWTc+HChYahbvEnmXBJxMaNG3HGGWfg5ptvximnnMJvHzNmDC677DJMmTIFM2bMwIoVKzBjxgzcfffd/TqOJUuWoLS0lP8MGTKkX/tLBaNO5E67jV8sM5GBYqJol4ED9UVTBzY3dqjb+g0ElJUcqJiAYq6buDROo08p4VlVQCkhcsGBog9VgshrWCdyJ/2tm0pWHajrrrsO8+fPT7rNyJEj09rnZ599hpNOOgk/+clPcNNNN/W6/dSpU7FmzRoAQFVVFex2O5qamjTbNDU1oa6uLuE+Fi1ahAULFvDffT5fxkWUWyjhhYTFbdnF0GwHSpZlQUApDow/FME1T6xHRJYhx/SaJAGynMCBYhmoAZ6F1xfKCvSz8FQHii1HY9VGmkobA8GBIlufIPIaO3egrPGZZRWyKqCqq6tRXV1t2v42bdqEE088EfPmzcPtt9+e0mPWr1+P+nql87LL5cKUKVOwevVqzJ07FwAQjUaxevXquCC6iNvthts9sMtf8DYGEW0GijtQJmegekIRLhwa2v0IR6JY+/U+vLxJ2wJi5iHVeGNLc5yACkeivATIlpvJZZgD1RWMIBSJajJQDKs4UPpxepw2zdI2FCIniPxGXcqFviyZiWUyUDt27EBrayt27NiBSCSC9evXAwBGjx6NoqIibNy4ESeeeCJmz56NBQsW8N5Odrudi7Rly5ZhxIgROOyww+D3+3H//ffj9ddfx6uvvsqfZ8GCBZg3bx6OPPJITJ06FcuWLUNXVxeflZcruJ3qLDwmlhw2sY2BuQ6UWJKLRGU0+vz4IlayG1lVCKfdhmKPA3MnH2QooMQSGBMnuUyJMMYmn5+vfyfitoqAMsxAURsDgjhQoKVcMoNlBNTixYvx8MMP898nT54MAHjjjTcwc+ZM/POf/0RzczMeffRRPProo3y7YcOG4ZtvvgGgzLK77rrrsHv3bni9XkycOBGvvfYaTjjhBL79Oeecg+bmZixevBiNjY2YNGkSXn755bhgebYRG2lqlnLJ0Cy8Dp0g2rW/B1uaFAH1vckH4WcnHQwAeOerFgDxGSjWiLLY47DEgpZ2m4RijwMd/jC27zOedWgVB8rpMJiFpwmR04cqQeQzdlrKJSNY4woApf+TLMtxPzNnzgQA3HLLLYb3M/EEADfccAO2bt2Knp4e7Nu3D2+88YZGPDGuuuoqbN++HYFAAO+99x6mTZs2QEeZOi6DELnLLmWsD5ReEO3a34MvYgLqkLpifjsrDXXpBBfro2SF/BODOWXf7OsyvN/aGSjFgXLYlMkaBEHkL9RIMzNY4wpAxKEKqAiCEbWNAbtYhkyehdehE1A79nVh695OAMAhtfECSu9YMQfKCvknBhNQzIESc0OAdRwoUejZJCUrxxwoykQQRP7DFnCvLBrYrG6+Y5kSHqFFMwsvrLYxcGTKgQpoQ9Rrv94HfygKt8OGoRVefnuRR3WgZFnm7gabxVZmIQeKrYf3TYviQI2qKcKGnW38fqsIKNGBKnDaIUkSz0BRDyiCyH+unz0Gxx9SjVnjciuKYnXo09OiuAzaGDjtNr7adlQGoia6UHoHii3ZcnBtkaauzlyaqKzM3GOoJTzrOlA1xW5NAN4qJTxR6Hlikw/Y60QOFEHkP5VFbpw6oZ5m3JoMnU2Lwi7emgyUQ9JcEEMmzsRjs+rqSjwAFIEEaMt3gOJwMD0l5qZYCc9KDhQXUK2KA1VW4ER1sWqBW8eBUt8TTECxPlDkQBEEQfQN+vS0KKyNgeJAxWegAHN7QTEH6tB6rWAaoxNQkiQZ5qCsGSJXxuoPKUK0vNCFqiJ1/NYRUKIDpfz/4JoiHFRWgOMOqcrWsAiCICwNZaAsithIkzlQDptNM8vCzG7kzIEaWV2ENVtbuGjTO1CAUh7y+cOamXj7u2Ih8kLrlfDE36uLPfx3q/SB0mSgYtmnQrcD/7vhBD47hyAIgkgPa1wBiDjcwiw8sYRn1wgo8x2oEo8TB5UV8NvFFgYMFiTXlvCsFyLXC6hyr86Bstv1D8lJ7Db1feFxqGMm8UQQBNF3SEBZFO1aeGoJT5KEXlAZyEAVeRwYXK7MuityOzCo1BO3rXEJz3ptDMq8egGlzUDpG1TmMuw9UeCyhugjCILIdUhAWRRxFl5QmIUHqMFgczNQaifxweWKA3VIbZFhE8ZCg2aa+y2ZgdKV8LxOVAl9VKwyCw9Qx+p2kIAiCIIwA8pAWRSjTuRcQNklIGRyBipWjit2OzC6pggAMHFwmeG2xayEFxNQsixzB0rv6uQyRiW8QEg9p1YJkQPqWMmBIgiCMAcSUBbFZdBIk7kMTEiFTewDJZbwzps2DBWFLpwwpsZwW17Ci4mu7mCEu2RWdqDKvE5EhHNqJQHF3hMeC42ZIAgilyEBZVFYKSYYjvJlW1gmh83EM9OBYmKoyO1AgcuOM48YnHBbfQmPle9cdhvvgG0FSuMyUC5IUEuWbouEyAFBQDmtM2aCIIhchgSURdGU8KJqGwNAcKAylIHqjWK3toQnlu+stHBtkcsBm6Q0DfU4bfA47agqkjCo1IOoDBS6rSNGKEROEARhLiSgLIrYB0p/m8PkWXiyLHMxVOzpPcNUpMtAWTFADijT/EsLnNjfHUJZrKmmw27DK9ceh6is/N8qUAmPIAjCXOjT1KK4nfEvHSvhsYulWX2gekIRvnQLyzclg5XwWPB8vwUD5AyWgxLHXuxxxuWjch3W9sJDDhRBEIQpkICyKEZT6NU2BjEHyiQBxYSQJCGlDFNRXAmPNdG0lugAjAWUFVEdKBJQBEEQZkACyqIYCSgmnLgDZVIJzycEyFPJMLGcVJcuA2W1Eh4AlMbGbMWxi7D3BGWgCIIgzIEElEWx2SSNiHLFupADagaKtTfoL8xJKkkh/wQAhS5tJ3IrLuPCyBcHqi7WMb7eoHM8QRAEkT4UIrcwLodN6EKuOkNOm7l9oDoFByoV9GvhWXEZF0ZloSv2r7uXLXObxd8Zh7mTD8Kxo6uyPRSCIIi8gASUhXE5bEBA+b9TmF3FHSiT+kB1BhQBVJRCCwMAKHYrQknfB8qKZbAfTx+GQDiKc741JNtD6RflhS4cf0h1todBEASRN1AJz8KIJTzWAwpQp9f3JUS+rzOA+//3NfZ1BvhtvjQdKNYfqSsYQSQqW3oW3qjqIiw5cwKGVHizPRSCIAgihyABZWHEVgYuTQmv732gHnrnG/z2xc/xyNrt/Da+Dl6KDpToVHUFw3wWXnmh9RwogiAIgjCCBJSFER0o4xJe+g7U7rYeAECL4ECpTTRTE1Buh51nsroCYezvYiU86zlQBEEQBGEECSgLIy5m67QblfDSd6CY2GH5JUBYSDjFEp64bVt3iJcArTgLjyAIgiCMIAFlYdwJBJRawkvfgWplAioY4bepCwmn7iCxMt6emKMFAGUW695NEARBEIkgAWVhRAdKzEA5+rGUyz4DByqdhYQZrBfU5sYOAEo/JSutHUcQBEEQyaArmoVxCctyaBwotphwf0p4ggPFS3hpCCgmtp5bvwcAMG1ERdpjIQiCIIhchQSUhXEbBMcBcSmX9BwofyjChZMmA8Vm4fUhA7WlSXGgTh5Xm9ZYCIIgCCKXIQFlYRKGyG2shJeeA8UaXgJAt1GIPJ0SniC2bBJw4tiatMZCEARBELkMCSgL49athcdIp4S3cXc7voi5RPs6VQHVqclAsTYGqYfAxbzUlGHlqCyy9lIoBEEQBCFCAsrCJG5jkFofqO5gGGctfwc/+MtahCNRrQMVjECWlcezEHlf2hgAVL4jCIIg8g9aC8/CaNoYOOJLeL11Im/tCsIfisIfimJvR4C3MFAeKyMQjsLtsKXdSBPQlvBOHleX8uMIgiAIwgqQgLIwWgdKivt/b2vhdQsz7fa09WgEFLs/EpXBsuh9caBGVRdiRFVhyo8jCIIgCCtAJTwLo+0DFd+JvLcSnjjTbreBgOoKhNHeo5TvHDYJXpcdqXLyuFqMqS3GNbMOSfkxBEEQBGEVyIGyMO4EfaAcKS4m3BVQHSgjAdUZCEOKGVulBU5IkoRUGVZZiFeuPS7l7QmCIAjCSljGgbr99tsxY8YMeL1elJWVGW4jSVLczxNPPKHZ5s0338QRRxwBt9uN0aNH46GHHorbz3333Yfhw4fD4/Fg2rRpeP/99zNwRP3H1UsfqN5KeF1B1YEyLuGF4etRtimhZVgIgiAIgmMZARUMBnH22WfjiiuuSLrdgw8+iIaGBv4zd+5cft+2bdtw2mmn4YQTTsD69etxzTXX4JJLLsErr7zCt1m5ciUWLFiAm2++GevWrcPhhx+O2bNnY+/evZk6tD7jStDGQJ2Fl9yB6tYIKL+BAxWBL1bCK0kjQE4QBEEQ+Y5lroq33norABg6RiJlZWWoqzOe9bV8+XKMGDECS5cuBQAceuihWLNmDe6++27Mnj0bAHDXXXfh0ksvxYUXXsgf8+KLL2LFihVYuHChSUdjDm5nosWE2Sw8xYG69flNWPNlC574yVGafkydYglvfw+istax6g6E0RNStiEHiiAIgiBULONApcqVV16JqqoqTJ06FStWrOC9jABg7dq1mDVrlmb72bNnY+3atQAUl+ujjz7SbGOz2TBr1iy+TS6hbZ6Z2IF66dMGfLm3E/+OrUvHELuN72nr4X2gaooVkdUphMhJQBEEQRCEimUcqFT4zW9+gxNPPBFerxevvvoqfvrTn6KzsxM///nPAQCNjY2ordU2daytrYXP50NPTw/279+PSCRiuM3mzZsTPm8gEEAgEOC/+3w+E48qMZo2Bg41A+XQZaD8IUVIvfDJHlx0zAi+nbhgcEcgjI7YIQyt8GJvRwDdwYiagUqjCzlBEARB5DtZdaAWLlxoGPwWf5IJFz2//vWvcfTRR2Py5Mn45S9/iRtuuAF33nlnBo9AYcmSJSgtLeU/Q4YMyfhzAtpGmho3yqZ1oPyxMty6HW3Ytb+bbye2MRAZXF4AQHGgfH7mQOWV1iYIgiCIfpFVAXXdddfh888/T/ozcuTIPu9/2rRp2LVrF3eH6urq0NTUpNmmqakJJSUlKCgoQFVVFex2u+E2iXJVALBo0SK0t7fzn507d/Z5zOmQqI0B+38oKiMa6yjOePGTBv5/MUTOKHY7UOZ18fvVEDk5UARBEATByKqtUF1djerq6oztf/369SgvL4fbrWR6pk+fjpdeekmzzapVqzB9+nQAgMvlwpQpU7B69Wo+ey8ajWL16tW46qqrEj6P2+3mzzGQ9LYWXjgS1YgnAHj+kz247PhRALR9oBgVRS4Uuu38fuZAlVIGiiAIgiA4lqnL7NixA62trdixYwcikQjWr18PABg9ejSKiorw/PPPo6mpCUcddRQ8Hg9WrVqF//u//8MvfvELvo/LL78c9957L2644QZcdNFFeP311/Hkk0/ixRdf5NssWLAA8+bNw5FHHompU6di2bJl6Orq4rPycolU+kCxWXQAYLdJ2Ljbh29aujC8qpCX8LwuO1/WpdzrgtelvC26KEROEARBEIZYRkAtXrwYDz/8MP998uTJAIA33ngDM2fOhNPpxH333Ydrr70Wsixj9OjRvCUBY8SIEXjxxRdx7bXX4p577sHgwYNx//338xYGAHDOOeegubkZixcvRmNjIyZNmoSXX345LlieCyTKQLFO5KFolOefXHYbpo2swP++bMHqzXtx8TEjeCPNg2uKsGFXOwCgstDF17HrEhtpUh8ogiAIguBY5qr40EMPJe0BNWfOHMyZM6fX/cycORMff/xx0m2uuuqqpCW7XCFxCU91oJiAcjttOKS2GP/7sgV7O/wA1MWED64t5gKqvNDF17zrFEp45EARBEEQhEre9YE6kND2gZLi/h+ORHkJz+O0oywmglgwnJXwDqkt4o8VHajuAIXICYIgCMIIElAWxu0UZuGJeSibOguP9YAqcNpR6lVEUFs3E1AxB6qmmD+2vNAFb0xAdfjD6IiJLAqREwRBEIQKCSgLk2gtPNGB8nMHysZFEAuGswzU0EovLwdWFLpQFJuF19ThB2vkXkwZKIIgCILgkICyMOlkoAqcdi6g2rpDkGWZZ6CK3Q4MKvUAACq8LhTGHCjmVLkdNngEt4sgCIIgDnRIQFkYd4I2BtpZeEoJz+208waZ7T0hBMJRRGKLDXvdDlxy7EgcM7oKR42qRKFL6zZRgJwgCIIgtFBdxsIkLuHF94ESQ+TtPSHNMi4FTjvOP2oYzj9qGAAgqGu+SfkngiAIgtBCDpSFsdkknncy7EQeVQVUgZCB6hQaZBY47bDbJHG3vI0Bg3pAEQRBEIQWElAWpyCWTfI4xcWE1f93+sOx++2aUlxDu9ILiuWdRNwOGy8DAlTCIwiCIAg9ZC1YnOvnjMXXzZ0YWuHlt4l5qM6A4jR5HIrTVOxxoMMfxu62HgDg696JSJIEr8sOn591IScBRRAEQRAiJKAszo9juSURsZzXERNBBbGyXJnXiQ5/GHtiAsrrMn4LFLkdXEBRBoogCIIgtFAJLw8Ru5KzEp47VuJjYogJqCIDBwoAb6YJACUFpLMJgiAIQoQEVB4iSRIPhjMXiWWlygqUVgZ72pQMVCIHSsxGUQmPIAiCILSQgMpTWAicZ6BiAoo7UO2JM1CA1pmiEDlBEARBaCEBlaewHFRnrN+TJ9Z0k62Hx0p4+qaZDNGZIgeKIAiCILSQgMpT2Ew8fYicOVCsQ7lRGwNACZEzKEROEARBEFpIQOUpjlgvKLEPFADejZyhb5ppdDuFyAmCIAhCCwmoPIXNxOuIlfDcDq0DxUjFgaISHkEQBEFoIQGVp7ASHlvXTuwDJVKY0IES2xiQgCIIgiAIERJQeYq4nAughsj1YsibwIESZ+fRWngEQRAEoYUEVJ4iLucCiBkol+b2RLPwWGmv0GWHw05vE4IgCIIQoStjnuLQOVB8Fp6+hJegDxQTUFS+IwiCIIh4SEDlKU69A+UwnoWXKEReHLudWhgQBEEQRDwUbslTnLqym8el/O512eGwSQhHZf67EUeNrMRpE+txyrjazA6UIAiCICwICag8JVEGSpIklHmdaOkMAtC2KxApcNlx37lHZHaQBEEQBGFRqISXp8Q5UA7VaRLLcokWEyYIgiAIIjEkoPIUtpgwANhtkiYTJQqoRCFygiAIgiASQwIqTxFbD3gcNkiSKqDKvEorA0kCCpwkoAiCIAgiXUhA5Smi4+TRiSTmQBW6HBphRRAEQRBEapCAylPEPlCJBFSiGXgEQRAEQSSHBFSe4tA4UNqXmTtQCWbgEQRBEASRHBJQeYoziQPFFhSmADlBEARB9A0SUHmK6EDpg+IVhUqIPFEPKIIgCIIgkkNX0DxF7AOld6BmjqnBGZMGYe7kgwZ6WARBEASRF5CAylPEPlBGIfJ7fjh5oIdEEARBEHkDlfDyFE0fKCe9zARBEARhJpa5st5+++2YMWMGvF4vysrK4u5/6KGHIEmS4c/evXsBAG+++abh/Y2NjZp93XfffRg+fDg8Hg+mTZuG999/fyAO0VSS9YEiCIIgCKJ/WEZABYNBnH322bjiiisM7z/nnHPQ0NCg+Zk9ezaOP/541NTUaLbdsmWLZjvx/pUrV2LBggW4+eabsW7dOhx++OGYPXs2F2FWQcxAUbdxgiAIgjAXy2Sgbr31VgCK02REQUEBCgoK+O/Nzc14/fXX8cADD8RtW1NTY+hiAcBdd92FSy+9FBdeeCEAYPny5XjxxRexYsUKLFy4sH8HMYAk6wNFEARBEET/yNsr6yOPPAKv14uzzjor7r5Jkyahvr4eJ598Mt5++21+ezAYxEcffYRZs2bx22w2G2bNmoW1a9cOyLjNIlkfKIIgCIIg+kfeCqgHHngA5557rsaVqq+vx/Lly/H000/j6aefxpAhQzBz5kysW7cOANDS0oJIJILa2lrNvmpra+NyUiKBQAA+n0/zk20clIEiCIIgiIyRVQG1cOHChMFv9rN58+a097t27Vp8/vnnuPjiizW3jxkzBpdddhmmTJmCGTNmYMWKFZgxYwbuvvvufh3HkiVLUFpayn+GDBnSr/2ZgSNJHyiCIAiCIPpHVjNQ1113HebPn590m5EjR6a93/vvvx+TJk3ClClTet126tSpWLNmDQCgqqoKdrsdTU1Nmm2amppQV1eXcB+LFi3CggUL+O8+ny/rIsppowwUQRAEQWSKrAqo6upqVFdXm7rPzs5OPPnkk1iyZElK269fvx719fUAAJfLhSlTpmD16tWYO3cuACAajWL16tW46qqrEu7D7XbD7Xb3e+xm4qBZeARBEASRMSwzC2/Hjh1obW3Fjh07EIlEsH79egDA6NGjUVRUxLdbuXIlwuEwzj///Lh9LFu2DCNGjMBhhx0Gv9+P+++/H6+//jpeffVVvs2CBQswb948HHnkkZg6dSqWLVuGrq4uPivPKlAfKIIgCILIHJYRUIsXL8bDDz/Mf588WVmK5I033sDMmTP57Q888ADOPPNMwzYFwWAQ1113HXbv3g2v14uJEyfitddewwknnMC3Oeecc9Dc3IzFixejsbERkyZNwssvvxwXLM91HDZyoAiCIAgiU0iyLMvZHkS+4fP5UFpaivb2dpSUlGRlDK9sasRlf/8IAPD4pdMwY1RVVsZBEARBEFYhnes3pYvzFCrhEQRBEETmIAGVp1AJjyAIgiAyBwmoPIUaaRIEQRBE5iABlae4NI006WUmCIIgCDOhK2ueQn2gCIIgCCJzkIDKUxw2KuERBEEQRKYgAZWnOAUHyu2gl5kgCIIgzISurHkKC5F7nDZIktTL1gRBEARBpINlOpET6TGswospw8pxSG1R7xsTBEEQBJEWJKDyFIfdhqevmJHtYRAEQRBEXkIlPIIgCIIgiDQhAUUQBEEQBJEmJKAIgiAIgiDShAQUQRAEQRBEmpCAIgiCIAiCSBMSUARBEARBEGlCAoogCIIgCCJNSEARBEEQBEGkCQkogiAIgiCINCEBRRAEQRAEkSYkoAiCIAiCINKEBBRBEARBEESakIAiCIIgCIJIExJQBEEQBEEQaeLI9gDyEVmWAQA+ny/LIyEIgiAIIlXYdZtdx5NBAioDdHR0AACGDBmS5ZEQBEEQBJEuHR0dKC0tTbqNJKcis4i0iEaj2LNnD4qLiyFJkqn79vl8GDJkCHbu3ImSkhJT950L5PvxAXSM+UC+Hx+Q/8eY78cH0DH2BVmW0dHRgUGDBsFmS55yIgcqA9hsNgwePDijz1FSUpK3fxBA/h8fQMeYD+T78QH5f4z5fnwAHWO69OY8MShEThAEQRAEkSYkoAiCIAiCINKEBJTFcLvduPnmm+F2u7M9lIyQ78cH0DHmA/l+fED+H2O+Hx9Ax5hpKEROEARBEASRJuRAEQRBEARBpAkJKIIgCIIgiDQhAUUQBEEQBJEmJKAIgiAIgiDShASUhbjvvvswfPhweDweTJs2De+//362h9QnlixZgm9961soLi5GTU0N5s6diy1btmi2mTlzJiRJ0vxcfvnlWRpx+txyyy1x4x87diy/3+/348orr0RlZSWKiorw/e9/H01NTVkccfoMHz487hglScKVV14JwJqv4X//+19897vfxaBBgyBJEp599lnN/bIsY/Hixaivr0dBQQFmzZqFL7/8UrNNa2srzjvvPJSUlKCsrAwXX3wxOjs7B/AoEpPs+EKhEH75y19iwoQJKCwsxKBBg3DBBRdgz549mn0Yve533HHHAB9JYnp7DefPnx83/jlz5mi2seprCMDwb1KSJNx55518m1x/DVO5RqTyGbpjxw6cdtpp8Hq9qKmpwfXXX49wOGzaOElAWYSVK1diwYIFuPnmm7Fu3TocfvjhmD17Nvbu3ZvtoaXNW2+9hSuvvBLvvvsuVq1ahVAohFNOOQVdXV2a7S699FI0NDTwn9///vdZGnHfOOywwzTjX7NmDb/v2muvxfPPP4+nnnoKb731Fvbs2YMzzzwzi6NNnw8++EBzfKtWrQIAnH322Xwbq72GXV1dOPzww3HfffcZ3v/73/8ef/zjH7F8+XK89957KCwsxOzZs+H3+/k25513HjZt2oRVq1bhhRdewH//+1/85Cc/GahDSEqy4+vu7sa6devw61//GuvWrcMzzzyDLVu24PTTT4/b9je/+Y3mdf3Zz342EMNPid5eQwCYM2eOZvz/+Mc/NPdb9TUEoDmuhoYGrFixApIk4fvf/75mu1x+DVO5RvT2GRqJRHDaaachGAzinXfewcMPP4yHHnoIixcvNm+gMmEJpk6dKl955ZX890gkIg8aNEhesmRJFkdlDnv37pUByG+99Ra/7fjjj5evvvrq7A2qn9x8883y4YcfbnhfW1ub7HQ65aeeeorf9vnnn8sA5LVr1w7QCM3n6quvlkeNGiVHo1FZlq3/GgKQ//Wvf/Hfo9GoXFdXJ9955538tra2Ntntdsv/+Mc/ZFmW5c8++0wGIH/wwQd8m//85z+yJEny7t27B2zsqaA/PiPef/99GYC8fft2ftuwYcPku+++O7ODMwmjY5w3b558xhlnJHxMvr2GZ5xxhnziiSdqbrPSayjL8deIVD5DX3rpJdlms8mNjY18mz//+c9ySUmJHAgETBkXOVAWIBgM4qOPPsKsWbP4bTabDbNmzcLatWuzODJzaG9vBwBUVFRobn/sscdQVVWF8ePHY9GiReju7s7G8PrMl19+iUGDBmHkyJE477zzsGPHDgDARx99hFAopHk9x44di6FDh1r29QwGg3j00Udx0UUXaRbQtvprKLJt2zY0NjZqXrfS0lJMmzaNv25r165FWVkZjjzySL7NrFmzYLPZ8N577w34mPtLe3s7JElCWVmZ5vY77rgDlZWVmDx5Mu68805TyyIDwZtvvomamhqMGTMGV1xxBfbt28fvy6fXsKmpCS+++CIuvvjiuPus9BrqrxGpfIauXbsWEyZMQG1tLd9m9uzZ8Pl82LRpkynjosWELUBLSwsikYjmjQAAtbW12Lx5c5ZGZQ7RaBTXXHMNjj76aIwfP57ffu6552LYsGEYNGgQPvnkE/zyl7/Eli1b8Mwzz2RxtKkzbdo0PPTQQxgzZgwaGhpw66234thjj8XGjRvR2NgIl8sVd1Gqra1FY2NjdgbcT5599lm0tbVh/vz5/Darv4Z62Gtj9HfI7mtsbERNTY3mfofDgYqKCsu9tn6/H7/85S/xox/9SLNI689//nMcccQRqKiowDvvvINFixahoaEBd911VxZHmzpz5szBmWeeiREjRuCrr77CjTfeiFNPPRVr166F3W7Pq9fw4YcfRnFxcVw8wEqvodE1IpXP0MbGRsO/VXafGZCAIrLKlVdeiY0bN2ryQQA0eYMJEyagvr4eJ510Er766iuMGjVqoIeZNqeeeir//8SJEzFt2jQMGzYMTz75JAoKCrI4sszwwAMP4NRTT8WgQYP4bVZ/DQ9kQqEQfvCDH0CWZfz5z3/W3LdgwQL+/4kTJ8LlcuGyyy7DkiVLLLFkyA9/+EP+/wkTJmDixIkYNWoU3nzzTZx00klZHJn5rFixAueddx48Ho/mdiu9homuEbkAlfAsQFVVFex2e9wMg6amJvz/9u42JKq0jQP4f8ycZmxzTKdmyAxFa3UDKWuH2V6g2kyJ3vBDibVT2wtZRpS1UdD2RhmxWbAfrKCUKBIKJOiVTIuyzTZzKsqkaUdlYaKoNM3KbK79sI/n4aQ5TmnjtP8fHHDOue97rsM158w1M/fxmEwmH0X1+TIzM3Hq1CmUlJQgIiKiw7YWiwUA4HA4vkRoXc5gMGDo0KFwOBwwmUxobm5GXV2dqo2/5rOmpgZFRUVYtGhRh+38PYetuenoODSZTG0u7GhpacHz58/9JretxVNNTQ0uXLig+vapPRaLBS0tLaiurv4yAXax6OhohIeHK6/LryGHAHDlyhVUVVV5PC6BnpvDj71HdOYcajKZ2j1WW7d1BRZQfiAoKAiJiYm4ePGiss7tduPixYuwWq0+jOzTiAgyMzNRWFiI4uJiREVFeexjt9sBAGazuZuj6x6NjY149OgRzGYzEhMT0bt3b1U+q6qqUFtb65f5zMvLw4ABAzB16tQO2/l7DqOiomAymVR5e/nyJcrKypS8Wa1W1NXVoby8XGlTXFwMt9utFJA9WWvx9PDhQxQVFSEsLMxjH7vdjoCAgDY/e/mLv//+G8+ePVNel/6ew1YHDx5EYmIiEhISPLbtaTn09B7RmXOo1WrF3bt3VcVw6weC+Pj4LguU/EBBQYFotVrJz8+X+/fvy5IlS8RgMKiuMPAXGRkZEhISIpcuXRKXy6UsTU1NIiLicDhk69atcvPmTXE6nXLy5EmJjo6W8ePH+zjyzsvKypJLly6J0+mU0tJS+fHHHyU8PFyePHkiIiJLly6VyMhIKS4ulps3b4rVahWr1erjqL33/v17iYyMlHXr1qnW+2sOGxoapKKiQioqKgSA5OTkSEVFhXIV2s6dO8VgMMjJkyflzp07MmPGDImKipLXr18rYyQnJ8uIESOkrKxMrl69KrGxsZKWluarXVLpaP+am5tl+vTpEhERIXa7XXVstl61dO3aNdmzZ4/Y7XZ59OiRHDlyRIxGo/z0008+3rP/62gfGxoaZM2aNfLHH3+I0+mUoqIiGTlypMTGxsqbN2+UMfw1h63q6+tFr9dLbm5um/7+kENP7xEins+hLS0tMnz4cElKShK73S7nzp0To9Eo69ev77I4WUD5kd9//10iIyMlKChIvv/+e7l+/bqvQ/okANpd8vLyRESktrZWxo8fL/379xetVisxMTGydu1aqa+v923gXpg9e7aYzWYJCgqSQYMGyezZs8XhcCjbX79+LcuWLZPQ0FDR6/Uya9YscblcPoz405w/f14ASFVVlWq9v+awpKSk3demzWYTkX//lcHGjRtl4MCBotVqZdKkSW32/dmzZ5KWliZ9+/aVfv36yYIFC6ShocEHe9NWR/vndDo/emyWlJSIiEh5eblYLBYJCQmRPn36SFxcnOzYsUNVfPhaR/vY1NQkSUlJYjQapXfv3jJkyBBZvHhxmw+i/prDVvv37xedTid1dXVt+vtDDj29R4h07hxaXV0tKSkpotPpJDw8XLKysuTdu3ddFqfmf8ESERERUSdxDhQRERGRl1hAEREREXmJBRQRERGRl1hAEREREXmJBRQRERGRl1hAEREREXmJBRQRERGRl1hAEdF/WnV1NTQajXKrme4wf/58zJw5s9vGJ6IvjwUUEfm1+fPnQ6PRtFmSk5M71X/w4MFwuVwYPnx4N0dKRF+TQF8HQET0uZKTk5GXl6dap9VqO9W3V69eXXZ3diL67+A3UETk97RaLUwmk2oJDQ0FAGg0GuTm5iIlJQU6nQ7R0dE4ceKE0vfDn/BevHiB9PR0GI1G6HQ6xMbGqoqzu3fvYuLEidDpdAgLC8OSJUvQ2NiobH///j1Wr14Ng8GAsLAw/PLLL/jwjllutxvZ2dmIioqCTqdDQkKCKiZPMRCR77GAIqKv3saNG5Gamorbt28jPT0dc+bMQWVl5Ufb3r9/H2fPnkVlZSVyc3MRHh4OAHj16hWmTJmC0NBQ/Pnnnzh+/DiKioqQmZmp9N+9ezfy8/Nx6NAhXL16Fc+fP0dhYaHqObKzs3H48GHs27cP9+7dw6pVqzB37lxcvnzZYwxE1EN02W2JiYh8wGazSa9evSQ4OFi1bN++XUT+vbP70qVLVX0sFotkZGSIiIjT6RQAUlFRISIi06ZNkwULFrT7XAcOHJDQ0FBpbGxU1p0+fVoCAgLk8ePHIiJiNptl165dyvZ3795JRESEzJgxQ0RE3rx5I3q9Xq5du6Yae+HChZKWluYxBiLqGTgHioj83oQJE5Cbm6ta179/f+Vvq9Wq2ma1Wj961V1GRgZSU1Nx69YtJCUlYebMmfjhhx8AAJWVlUhISEBwcLDSfsyYMXC73aiqqkKfPn3gcrlgsViU7YGBgRg1apTyM57D4UBTUxMmT56set7m5maMGDHCYwxE1DOwgCIivxccHIyYmJguGSslJQU1NTU4c+YMLly4gEmTJmH58uX47bffumT81vlSp0+fxqBBg1TbWie+d3cMRPT5OAeKiL56169fb/M4Li7uo+2NRiNsNhuOHDmCvXv34sCBAwCAuLg43L59G69evVLalpaWIiAgAMOGDUNISAjMZjPKysqU7S0tLSgvL1cex8fHQ6vVora2FjExMapl8ODBHmMgop6B30ARkd97+/YtHj9+rFoXGBioTLw+fvw4Ro0ahbFjx+Lo0aO4ceMGDh482O5Yv/76KxITE/Hdd9/h7du3OHXqlFJspaenY9OmTbDZbNi8eTOePn2KFStWYN68eRg4cCAAYOXKldi5cydiY2Px7bffIicnB3V1dcr433zzDdasWYNVq1bB7XZj7NixqK+vR2lpKfr16webzdZhDETUM7CAIiK/d+7cOZjNZtW6YcOG4cGDBwCALVu2oKCgAMuWLYPZbMaxY8cQHx/f7lhBQUFYv349qqurodPpMG7cOBQUFAAA9Ho9zp8/j5UrV2L06NHQ6/VITU1FTk6O0j8rKwsulws2mw0BAQH4+eefMWvWLNTX1ytttm3bBqPRiOzsbPz1118wGAwYOXIkNmzY4DEGIuoZNCIf/IMSIqKviEajQWFhIW+lQkRdinOgiIiIiLzEAoqIiIjIS5wDRURfNc5SIKLuwG+giIiIiLzEAoqIiIjISyygiIiIiLzEAoqIiIjISyygiIiIiLzEAoqIiIjISyygiIiIiLzEAoqIiIjISyygiIiIiLz0D6k2RJgDGW5xAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "episodes_list = list(range(len(return_list)))\n",
    "plt.plot(episodes_list, return_list)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title(f'DDPG on {env_name}')\n",
    "plt.show()\n",
    "\n",
    "mv_return = rl_utils.moving_average(return_list, 9)\n",
    "plt.plot(episodes_list, mv_return)\n",
    "plt.xlabel('Episodes')\n",
    "plt.ylabel('Returns')\n",
    "plt.title(f'DDPG on {env_name}')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ef87216b",
   "metadata": {},
   "outputs": [],
   "source": [
    "rl_utils.play_game(env_name, agent)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
